# templates

name: Auto-Generate LinkedIn Posts from Articles with Dumpling AI and GPT-4o
author_name: Yang
author_username: yang
categories: []
created_at: 2025-06-03T22:28:16.392Z
updated_at: 2025-06-03T22:28:16.392Z
url: https://n8n.io/workflows/4631
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  👤 Who is this for?

  This workflow is ideal for social media managers, personal brand strategists, ghostwriters, and founders who want to post regularly on LinkedIn without spending hours writing from scratch. It’s also useful for marketing agencies and assistants looking to automate consistent post creation using curated articles as source material.

  🧩 What problem does this workflow solve?

  Manually reading multiple articles, extracting key insights, and writing a clean, professional LinkedIn post is a time-consuming process. This workflow automates everything: from pulling topics, finding related articles, summarizing them using AI, and even generating a matching image to accompany the post. It ensures faster content turnaround, more consistency, and less manual effort.

  🔁 What this workflow does

  This workflow starts manually and retrieves one topic marked as “To do” from a Google Sheet. That topic is used as a search term for Dumpling AI’s search endpoint, which scrapes and returns the top three article contents related to the topic. These articles are sent to a LangChain agent powered by GPT-4o, which analyzes and summarizes the content into a LinkedIn post in a friendly, insightful tone. It also generates an image prompt for the post.

  After generating the post and image prompt, the data is extracted using a Set node. The prompt is sent to Dumpling AI’s image generation endpoint, which returns an image URL. Finally, the post text, image prompt, image URL, and status update (“created”) are saved back to the original row in Google Sheets.

  🛠️ Workflow Breakdown

  Manual Trigger – Starts the automation.
  Google Sheets (Get Topic) – Searches for the first row in your content pipeline sheet where the “status” is “To do”.
  HTTP Request (Dumpling AI Search) – Uses the topic as a search query to pull 3 article contents using Dumpling AI’s API.
  Set LangChain GPT Model – Defines GPT-4o as the LLM for the LangChain Agent.
  LangChain Agent (Summarize & Generate) – Summarizes all 3 articles and generates a LinkedIn post and a related image prompt.
  Set (Extract Data) – Extracts postText and imagePrompt from the LangChain agent output.
  HTTP Request (Dumpling Image Gen) – Sends imagePrompt to Dumpling AI’s image generation endpoint.
  Update Google Sheets – Writes the post, image prompt, and image URL back to the sheet and changes the row status to “created”.

  ⚙️ Setup Instructions

  Dumpling AI
     Sign up at Dumpling AI
     Get your API key and connect it in the HTTP Request nodes (Search and Image endpoints)
     Use the /search endpoint to retrieve article content
     Use the /generate-image endpoint to create the image

  Google Sheets
     Create a spreadsheet with columns: topic, status, postText, imagePrompt, imageURL
     Add sample topics and set their status to To do

  LangChain (GPT-4o)
     Connect your OpenAI credentials to n8n
     Make sure GPT-4o is available in your OpenAI account
     Use the LangChain node to process multi-input summarization and generate a social media caption

  Customize the Prompt (Optional)
     Adjust the Set node to tweak the input format sent to the LangChain agent
     Add constraints like tone, hashtags, or emojis to fit your brand style

  🧠 How to Customize This Workflow

  Change the content source (RSS feed, Notion DB, etc.) instead of Google Sheets
  Add a scheduler node to run this automatically every morning or weekly
  Use Airtable instead of Google Sheets for more control and filtering
  Send the final post to LinkedIn using the Buffer or LinkedIn API
  Add a Telegram or Slack notification when new content is ready for approval

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","social media","content creation","AI/ML integration"],"complexity":"medium","use_cases":["Auto-generate LinkedIn posts from curated articles","Content repurposing and summarization","Scale social media posting for personal brands and agencies","Generate matching images for posts"],"estimated_setup_minutes":30,"required_services":["Dumpling AI (search & image endpoints)","Google Sheets","OpenAI GPT-4o (via LangChain)"],"key_features":["Searches and scrapes top related articles for a topic","Summarizes multiple articles into a single LinkedIn post using a LangChain GPT-4o agent","Generates an image prompt and produces an image via Dumpling AI","Writes post text, image prompt, image URL and status back to Google Sheets","Manual trigger with easy option to add scheduling or publish integrations (Buffer/LinkedIn)"],"target_audience":["Social media managers","Personal brand strategists and founders","Marketing agencies and assistants/ghostwriters\",\"Content creators and growth teams"]}


name: Scrape Google Places via Dumpling AI and Auto-Save to Google Sheets
author_name: Yang
author_username: yang
categories: []
created_at: 2025-06-03T22:42:31.611Z
updated_at: 2025-06-03T22:42:31.611Z
url: https://n8n.io/workflows/4632
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?
  This workflow is perfect for lead generation experts, digital marketers, SEO professionals, and virtual assistants who need to quickly collect local business information based on specific search terms without manually navigating Google Places.

  What problem is this workflow solving?
  Manually searching Google Places for business leads is time-consuming and inconsistent. This workflow automates the entire process using Dumpling AI’s Google Places search endpoint, helping users collect accurate and structured business data and log it into a Google Sheet automatically.

  What this workflow does
  This workflow runs daily at 1 PM. It starts by reading a list of business-related search terms from a Google Sheet (for example, “dentists in Dallas”). Each term is sent to Dumpling AI’s search-places endpoint, which returns local business listings from Google Places. The data is split, structured, and logged row-by-row in a connected Google Sheet.

  Nodes Overview

  Run Every Day at 1 PM  
     A scheduled trigger that executes the workflow daily.

  Google Sheets (Input) – Fetch Search Terms from Sheet  
     Pulls a list of search terms from a Google Sheet. Each term should describe a business category and location (e.g., “coffee shops in Atlanta”).

  HTTP Request – Scrape Google Places via Dumpling AI  
     Sends each search term to Dumpling AI’s /search-places endpoint, returning data like business names, phone numbers, websites, ratings, and categories.

  Split In Batches – Split Places Result  
     Breaks the list of businesses returned for each search term into individual items for processing.

  Google Sheets (Output) – Save Each Business to Sheet  
     Saves the scraped data into a second Google Sheet. Each row contains:
     title
     address
     rating
     category
     phoneNumber
     website

  📝 Notes

  You must set up Dumpling AI and generate your API key from: Dumpling AI
  You can change the run schedule in the schedule node to fit your needs (e.g., weekly or hourly).

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","data extraction","integration","lead generation"],"complexity":"medium","use_cases":["Lead generation and prospecting","Local SEO research","Sales outreach list building","Business data enrichment","Automated data collection and logging"],"estimated_setup_minutes":15,"required_services":["Dumpling AI (Google Places /search-places endpoint)","Google Sheets (Google Workspace account)","Internet access / API connectivity"],"key_features":["Scheduled daily run (configurable)","Send search terms to Dumpling AI and receive Google Places results","Split batch results into individual business items","Auto-save structured business fields (title, address, rating, category, phoneNumber, website) to Google Sheets","Simple configuration of search terms via Google Sheets"],"target_audience":["Lead generation specialists","Digital marketers","SEO professionals / local search analysts」「Virtual assistants / operations teams"]}


name: Generate Captions from Autocomplete Ideas using Dumpling AI + GPT-4o
author_name: Yang
author_username: yang
categories: []
created_at: 2025-06-03T22:53:46.256Z
updated_at: 2025-06-03T22:53:46.256Z
url: https://n8n.io/workflows/4633
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  📌 Who is this for?

  This workflow is perfect for social media managers, content creators, digital marketers, and copywriters who want to save time and stay relevant by automatically generating fresh caption ideas based on trending search behavior.

  💡 What problem is this workflow solving?

  Manually coming up with engaging social media content is time-consuming and often hit-or-miss. This workflow leverages Google autocomplete to identify what users are searching for, then uses AI to convert those suggestions into short, engaging captions for use on platforms like Instagram, LinkedIn, or Twitter.

  ⚙️ What this workflow does

  This automation runs daily at noon and transforms trending search topics into ready-to-use captions:

  Run Every Day at 12 PM  
     A schedule trigger that activates the workflow once per day.

  Get Search Keywords from Google Sheet  
     Pulls a list of base search phrases from a Google Sheet which serve as the starting point for getting trending autocomplete terms.

  Fetch Autocomplete Suggestions (Dumpling AI)  
     Calls Dumpling AI’s get-autocomplete endpoint using the base phrase to return Google autocomplete suggestions.  
     API Reference →

  Format Suggestions into Array  
     Formats the list of returned suggestions into an array format that can be looped through.

  Loop Through Each Autocomplete Suggestion  
     Splits the array into individual suggestions to process each one separately.

  Generate Caption from Suggestion (GPT-4o)  
     Sends each suggestion to GPT-4o with a detailed system prompt to create a short, human-sounding, engaging caption under 280 characters.

  Save Keyword & Generated Caption to Google Sheet  
     Saves both the original search suggestion and the generated caption to another tab in Google Sheets for content scheduling or review.

  This workflow combines real-time search trend data with the power of AI to keep your social media feed fresh, relevant, and consistent — all without lifting a finger.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","content-generation","social-media","ai-integration","data-processing"],"complexity":"medium","use_cases":["Generate short social media captions from trending search queries","Automate daily content ideation based on Google autocomplete","Build a caption bank in Google Sheets for scheduling/review","Convert search intent into concise, platform-ready copy"],"estimated_setup_minutes":20,"required_services":["Google Sheets","Dumpling AI (autocomplete API)","OpenAI (GPT-4o)"],"key_features":["Daily scheduled run","Pulls base phrases from Google Sheets","Fetches Google autocomplete suggestions via Dumpling AI","Formats and loops through suggestions","Generates sub-280 character captions using GPT-4o with a system prompt」「Saves suggestions and captions back to Google Sheets for review"],"target_audience":["Social media managers","Content creators","Digital marketers','Copywriters"]}


name: Reschedule Google Calendar Appointments with Stream Deck (15/30/60 min)
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-03T23:24:33.784Z
updated_at: 2025-06-03T23:24:33.784Z
url: https://n8n.io/workflows/4634
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  ⏰ Move All Appointments 15/30/60 Minutes Later Via Stream Deck

  Running a bit behind? 😅

  Shift your day's remaining Google Calendar appointments by 15, 30, or 60 minutes with one press of a stream deck button!

  tl;dr

  This template is your lifesaver for those days when things get hectic. With dedicated buttons on your Stream Deck, you can instantly push all subsequent Google Calendar appointments for the current day forward by 15, 30, or 60 minutes, automatically notifying all attendees.

  Why You'll Love This Workflow ❤️:

      One-Click Reschedule: No more manually editing each calendar event. One press, and your day is adjusted!
      Stream Deck Powered: Integrates seamlessly with your Elgato Stream Deck using the API Ninja plugin.
      Flexible Delays: Choose between 15, 30, or 60-minute adjustments with separate buttons.
      Smart Event Fetching: Automatically grabs all remaining appointments for the current day from your specified Google Calendar.
      Attendee Notifications: Keeps everyone in the loop by sending standard Google Calendar update notifications.
      Peace of Mind: Your "graceful delay" button when you need a few extra minutes.

  Perfect For 🧑‍💻:

      Busy professionals managing a packed schedule.
      Streamers and content creators who need to adjust live sessions or meetings on the fly.
      Anyone who juggles back-to-back Google Calendar appointments and uses a Stream Deck for peak efficiency.

  Streamlined Setup Guide 🛠️:

  1️⃣ Install the "API Ninja" plugin

  2️⃣ n8n Webhook Configuration:
  (choose a username and password).

  3️⃣ Stream Deck Buttons:
  Create three "API Ninja" buttons on your Stream Deck.
  Configure each button to make a POST request to its corresponding n8n webhook

  4️⃣ Google Calendar Connection:
  In each of the "Get the Events..." and "Push All Meetings..." Google Calendar nodes, select your Google Calendar account (or create a new credential).
  Update the "Calendar" field

  5️⃣ Activate & Test! Your Stream Deck buttons should now be ready to dynamically adjust your day.

  Important Notes 📝:

      Calendar Selection: Ensure you've correctly selected your target calendar in all Google Calendar nodes.
      Error Handling: The workflow includes basic error handling to respond with a 500 error if issues occur (like not finding events), otherwise, it responds with a 200 success code.
      Attendee Impact: Remember this will move all remaining events for the day and send updates to all attendees of those events.

  Take control of your schedule with this powerful Stream Deck and n8n automation. Never stress about manually pushing meetings again! ✨

nodes_used:
  ["n8n-nodes-base.googleCalendar","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.googleCalendar","n8n-nodes-base.googleCalendar","n8n-nodes-base.googleCalendar","n8n-nodes-base.googleCalendar","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.googleCalendar","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","productivity","calendar"],"complexity":"medium","use_cases":["Shift all remaining Google Calendar events for the day by a chosen delay (15/30/60 minutes)","Notify attendees automatically after rescheduling","Quickly adjust schedules from a Stream Deck button","Automate last‑minute schedule changes for live sessions or meetings","Centralize one‑click calendar management"],"estimated_setup_minutes":15,"required_services":["Google Calendar account / API access","n8n instance (with webhook access)","Elgato Stream Deck with API Ninja plugin (or equivalent HTTP plugin)","Publicly reachable webhook endpoint or n8n cloud"],"key_features":["One‑click reschedule via Stream Deck","Three preset delay options: 15, 30, 60 minutes","Automatically fetches remaining events for the current day","Updates events in Google Calendar and sends attendee notifications","Uses n8n webhooks and basic error handling (200/500 responses)"],"target_audience":["Busy professionals and executives","Streamers and content creators","Operations/admin assistants managing meetings at scale\",\"Developers or power users configuring n8n automations"]}


name: Extract & Enrich LinkedIn Comments to Leads with Apify → Google Sheets/CSV
author_name: Saverflow AI
author_username: saverflowai
categories: []
created_at: 2025-06-04T02:39:54.846Z
updated_at: 2025-06-04T02:39:54.846Z
url: https://n8n.io/workflows/4635
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-30 08:33:37
description:
  🚀 LinkedIn Comments to Leads Extractor & Enricher (Apify) → Google Sheets / CSV

  Overview

  Automate LinkedIn lead generation by scraping comments from targeted posts and enriching profiles with detailed data

  This n8n workflow automatically extracts leads from LinkedIn post comments using Apify's powerful scrapers (no LinkedIn login required), enriches the data with additional profile information, and exports everything to Google Sheets or CSV format.

  ✨ Key Features

  🔍 No Login Required: Scrape LinkedIn data without sharing credentials
  💰 Cost-Effective: First 1,000 comments are free with Apify
  📊 Data Enrichment: Enhance basic comment data with full profile details
  📈 Export Options: Choose between Google Sheets or CSV output
  🎯 Targeted Scraping: Focus on specific posts for quality leads

  🛠️ Apify Scrapers Used

  1. LinkedIn Post Comments Scraper
  Tool**: LinkedIn Post Comments, Replies, Engagements Scraper | No Cookies
  Pricing**: $5.00 per 1,000 results
  Function**: Extracts all comments and engagement data from specified LinkedIn posts

  2. LinkedIn Profile Batch Scraper
  Tool**: LinkedIn Profile Details Batch Scraper (No Cookies Required)
  Pricing**: $5.00 per 1,000 results
  Function**: Enriches scraped profiles with detailed information

  &gt; 💡 Free Tier: Apify provides 1,000 free scraped comments to get you started!

  📋 Prerequisites

  Required API Credentials

  Apify Token
     Add your APIFY_TOKEN to the workflow credentials
     Get your token from Apify Console

  Google Sheets Credentials (if using Sheets export)
     Configure OAuth credentials for Google Sheets integration
     Follow n8n's Google Sheets setup guide

  🔄 Workflow Process

  Default Mode: Form-Based Execution

  Manual Trigger → Launches the workflow
  Form Submission → User-friendly form for inputting LinkedIn post URLs
  Comment Scraping → Apify extracts all comments from specified posts
  Profile Enrichment → Additional profile data gathered for each commenter
  Data Processing → Creates unique, enriched lead list
  Google Sheets Export → Automatically populates your spreadsheet

  Result: You'll be redirected to a Google Sheets document containing all enriched leads

  Alternative Mode: CSV Export

  For users preferring CSV output:

  Disable: Form trigger nodes
  Enable: Manual trigger node
  Disable: Google Sheets export nodes
  Enable: CSV download nodes
  Configure: Add post IDs/URLs in "Set manual fields" node
  Execute: Run workflow and download CSV from the CSV node

  📊 Output Data Structure

  Your exported data will include:

  Basic Info**: Name, headline, location
  Profile Details**: Company, position, industry
  Engagement Data**: Comment content, engagement metrics
  Contact Info**: Available profile links and connections
  Enriched Data**: Additional profile insights from Apify

  💡 Pro Tips

  Quality over Quantity**: Target posts with high-quality, relevant engagement
  Monitor Costs**: Track your Apify usage to stay within budget
  Data Hygiene**: Regularly clean and deduplicate your lead lists
  Compliance**: Ensure your scraping activities comply with LinkedIn's terms of service

  🆘 Troubleshooting

  Common Issues:
  Authentication Errors**: Verify your Apify token is correctly configured
  Empty Results**: Check that your LinkedIn post URLs are valid and public
  Export Failures**: Ensure Google Sheets credentials are properly set up

  Need Help? Contact Saverflow.ai for support and custom workflow development.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.splitInBatches","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.convertToFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.noOp"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","lead generation"],"complexity":"complex","use_cases":["LinkedIn lead extraction from post comments","Sales prospecting and outreach list building","Recruiting and candidate sourcing","Market research and social listening","CRM enrichment and data hygiene"],"estimated_setup_minutes":45,"required_services":["Apify (LinkedIn scrapers)","Google Sheets (or CSV storage via Google Drive/S3/local)","Optional enrichment APIs (e.g., Clearbit, People Data Labs, FullContact, Hunter)","n8n"],"key_features":["Scrape LinkedIn post comments without requiring LinkedIn login (via Apify)","Enrich extracted profiles with additional data fields","Export results to Google Sheets or downloadable CSV","Batch processing and split-merge handling for large datasets","Deduplication and aggregation of leads before export (aggregate nodes)"],"target_audience":["sales reps and business development teams","growth marketers and demand gen","recruiters and talent sourcers (technical and non-technical) or staffing firms)"]}


name: Automate Social Media Content with AI for Instagram, Facebook, LinkedIn & X
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-06-04T03:00:43.654Z
updated_at: 2025-06-04T03:00:43.654Z
url: https://n8n.io/workflows/4637
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  AI Social Media Content Automation – n8n Workflow

  This workflow is built for creators, solopreneurs, SaaS founders, and agencies looking to automate their social media content process from idea to publication. It combines the power of OpenAI, Google Sheets, and official APIs for Instagram, Facebook, X (Twitter), and LinkedIn to deliver fully automated, brand-consistent social media posts — including text, images, hashtags, CTAs, and scheduling.

  No more switching tools, rewriting content, or forgetting to post. Just set it up once and let your brand grow automatically.

  🔧 What the Workflow Does
  Generates platform-specific post ideas based on your brand tone.
  Selects the best idea (or lets you manually input one).
  Writes tailored posts for Instagram, Facebook, X, and LinkedIn.
  Auto-generates platform-specific visuals using OpenAI (DALL·E) and uploads to Cloudinary.
  Publishes content directly using official platform APIs.
  Logs all actions to Google Sheets and optionally sends a summary email via Gmail.

  ⚙️ How It Works
  Trigger the workflow manually, on a schedule, or from a chatbot.
  AI generates multiple post ideas and filters the best one.
  Based on the selected idea, it generates full posts for each platform.
  Custom visuals are created using OpenAI and uploaded to Cloudinary.
  Final post content is merged and sent to Instagram, Facebook, X, and LinkedIn.
  Logs and optional reports are created in Google Sheets and Gmail.

  🛠️ Setup Steps
  Set up your accounts and credentials: OpenAI, Cloudinary, Gmail, Meta, LinkedIn, X, and Google Sheets.
  Import the workflow and subworkflow (Get Brand Brief) into n8n.
  Replace all placeholders (sheet IDs, access tokens, profile/page IDs, brand brief URLs).
  Optionally personalize prompts and output templates to match your brand voice.
  Setup time: ~30–45 minutes (including credentials and testing).

  Detailed configuration notes are included in sticky nodes throughout the workflow.

  📦 Included in Your Package
  JSON workflow file (main flow + brand brief subflow)
  Google Sheets templates for history logging
  Setup documentation (Markdown & PDF)
  Placeholder reference sheet

nodes_used:
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workflow_json_compressed:
  [encoded data, 5204 characters]

metadata_json:
  {"categories":["automation","integration","social media","content generation","marketing"],"complexity":"medium","use_cases":["Automated cross‑platform social posting (Instagram, Facebook, X, LinkedIn)","AI‑generated post ideas and platform‑specific copy","Auto‑generate and upload visuals (DALL·E → Cloudinary)","Scheduling and direct publishing via official APIs","Logging history and sending summary reports to Google Sheets/Gmail"],"estimated_setup_minutes":40,"required_services":["n8n","OpenAI (ChatGPT / DALL·E)","Cloudinary","Google Sheets","Gmail","Meta Graph API (Instagram & Facebook)","LinkedIn API","X (Twitter) API"],"key_features":["Generates brand‑consistent, platform‑specific post ideas and copy","Selects or accepts manual idea input","Auto‑creates visuals with OpenAI and uploads to Cloudinary","Publishes directly using official platform APIs","Logs actions to Google Sheets and optional Gmail summaries」「Includes reusable Brand Brief subworkflow and editable prompt templates"],"target_audience":["creators","solopreneurs","SaaS founders」「agencies」「social media managers」「marketers"]}


name: 🎙️ VoiceFlow AI: Telegram + Deepgram + OpenAI + Supabase Audio Assistant
author_name: RedOne
author_username: redone
categories: []
created_at: 2025-06-04T03:05:18.646Z
updated_at: 2025-06-04T03:05:18.646Z
url: https://n8n.io/workflows/4638
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🎙️ AI Audio Assistant with Voice-to-Voice Response

  Who is this for?
  Businesses, customer service teams, content creators, and organizations who want to provide intelligent voice-based interactions through Telegram. Perfect for accessibility-focused services, multilingual support, or hands-free customer assistance.

  What problem does this solve?
  Enables natural voice conversations with AI
  Breaks down language and accessibility barriers
  Provides instant voice responses to customer queries
  Reduces typing requirements for users
  Offers 24/7 voice-based customer support
  Maintains conversation context across voice interactions

  What this workflow does:
  Receives voice messages via Telegram bot
  Transcribes audio using Deepgram's advanced speech-to-text
  Processes transcribed text through AI agent with knowledge base access
  Generates intelligent responses based on conversation context
  Converts AI response to natural-sounding speech using Deepgram TTS
  Sends audio response back to user via Telegram
  Maintains conversation memory for contextual interactions

  🔧 Technical Architecture

  Core Components:
  Telegram Bot**: Receives and sends voice messages
  Deepgram STT**: Transcribes voice to text with high accuracy
  OpenAI GPT**: Processes queries and generates responses
  Supabase Knowledge Base**: Stores and retrieves business information
  Memory Management**: Maintains conversation context
  Deepgram TTS**: Converts text responses to natural speech

  Data Flow:
  Voice Message → Telegram API → File Download
  Audio File → Deepgram STT → Transcript
  Transcript → AI Agent → Response Generation
  Response → Deepgram TTS → Audio File
  Audio Response → Telegram → User

  🛠️ Setup Instructions

  Prerequisites
  Telegram Bot Token
     Create bot via @BotFather
     Get bot token and configure webhook

  Deepgram API Key
     Sign up at deepgram.com
     Get API key for STT and TTS services
     Note: Currently hardcoded in workflow

  OpenAI API Key
     OpenAI account with API access
     Configure in OpenAI Chat Model node

  Supabase Database
     Create Supabase project
     Set up knowledge_base table
     Configure API credentials

  Step-by-Step Setup

  Configure Telegram Bot
        Update telegramToken in "Prepare Voice Message Data" node
     Set correct bot token in Telegram nodes
     Test bot connectivity
     
  Set Up Deepgram Integration
        Replace API key in "Transcribe with Deepgram" node
     Update TTS endpoint in "HTTP Request" node
     Test voice transcription accuracy
     
  Configure Knowledge Base
        -- Create knowledge_base table in Supabase
     CREATE TABLE knowledge_base (
       id UUID DEFAULT gen_random_uuid() PRIMARY KEY,
       question TEXT NOT NULL,
       answer TEXT NOT NULL,
       category VARCHAR(100),
       keywords TEXT[],
       created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
     );
     
  Customize AI Prompts
     Update system message in "Telegram AI Agent" node
     Adjust temperature and max tokens in OpenAI model
     Configure memory session keys

  Test End-to-End Flow
     Send test voice message to bot
     Verify transcription accuracy
     Check AI response quality
     Validate audio output clarity

  🎛️ Configuration Options

  Voice Recognition Settings
  Model**: nova-2 (Deepgram's latest model)
  Language**: English (en) - can be changed
  Smart Format**: Enabled for better punctuation

  AI Response Settings
  Temperature**: 0.3 (conservative responses)
  Max Tokens**: 100 (adjust based on needs)
  Memory**: Session-based conversation context

  Text-to-Speech Settings
  Model**: aura-2-thalia-en (natural female voice)
  Alternative voices**: Available in Deepgram TTS API
  Audio Format**: Optimized for Telegram

  🔒 Security Considerations

  API Key Management
  // Current implementation has hardcoded tokens
  // Recommended: Use environment variables
  const telegramToken = process.env.TELEGRAM_BOT_TOKEN;
  const deepgramKey = process.env.DEEPGRAM_API_KEY;

  Data Privacy
  Voice messages are processed by external APIs
  Consider data retention policies
  Implement user consent mechanisms
  Ensure GDPR compliance if applicable

  📊 Monitoring & Analytics

  Key Metrics to Track
  Voice message processing time
  Transcription accuracy rates
  AI response quality scores
  User engagement metrics
  Error rates and failure points

  Recommended Logging
  // Add to workflow for monitoring
  console.log({
    timestamp: new Date().toISOString(),
    user_id: userData.user_id,
    transcript_confidence: transcriptData.confidence,
    response_length: aiResponse.length,
    processing_time: processingTime
  });

  🚀 Customization Ideas

  Enhanced Features
  Multi-language Support
     Add language detection
     Support multiple TTS voices
     Translate responses

  Voice Commands
     Implement wake words
     Add voice shortcuts
     Create voice menus

  Advanced AI Features
     Sentiment analysis
     Intent classification
     Escalation triggers

  Integration Expansions
     Connect to CRM systems
     Add calendar scheduling
     Integrate with help desk tools

  Performance Optimizations
  Implement audio preprocessing
  Add response caching
  Optimize API call sequences
  Implement retry mechanisms

  🐛 Troubleshooting

  Common Issues

  Voice Not Transcribing
  Check Deepgram API key validity
  Verify audio format compatibility
  Test with shorter voice messages

  Poor Audio Quality
  Adjust TTS model settings
  Check network connectivity
  Verify Telegram audio limits

  AI Responses Too Generic
  Improve knowledge base content
  Adjust system prompts
  Increase context window

  Memory Not Working
  Check session key configuration
  Verify user ID extraction
  Test conversation continuity

  💡 Best Practices

  Voice Interface Design
  Keep responses concise and clear
  Use natural speech patterns
  Avoid technical jargon
  Provide clear next steps

  Knowledge Base Management
  Regular content updates
  Clear categorization
  Keyword optimization
  Quality assurance testing

  User Experience
  Fast response times (&lt;5 seconds)
  Consistent voice personality
  Graceful error handling
  Clear capability communication

  📈 Success Metrics

  Technical KPIs
  Response time: &lt;3 seconds average
  Transcription accuracy: &gt;95%
  User satisfaction: &gt;4.5/5
  Uptime: &gt;99.5%

  Business KPIs
  Customer query resolution rate
  Support ticket reduction
  User engagement increase
  Cost per interaction decrease

  🔄 Maintenance Schedule

  Daily
  Monitor error logs
  Check API rate limits
  Verify service uptime

  Weekly
  Review conversation quality
  Update knowledge base
  Analyze usage patterns

  Monthly
  Performance optimization
  Security audit
  Feature updates
  User feedback review

  📚 Additional Resources

  Documentation Links
  Deepgram STT API
  Deepgram TTS API
  Telegram Bot API
  OpenAI API
  Supabase Documentation

  Community Support
  n8n Community Forum
  Telegram Bot Developers Group
  Deepgram Developer Discord
  OpenAI Developer Community

  Note: This template requires active API subscriptions for Deepgram and OpenAI services. Costs may apply based on usage volume.

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workflow_json_compressed:
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metadata_json:
  {"categories":["voice-assistant","automation","integration","AI-powered support","customer service"],"complexity":"complex","use_cases":["Voice-based customer support via Telegram","Accessibility and hands-free interactions","Multilingual voice assistants","Knowledge-base driven Q&A","24/7 automated voice responses"],"estimated_setup_minutes":60,"required_services":["Telegram Bot API","Deepgram (STT & TTS)","OpenAI (Chat/LLM)","Supabase (knowledge base)","n8n instance or compatible workflow runner"],"key_features":["Receives Telegram voice messages and downloads audio","Deepgram STT for accurate transcription","OpenAI agent for contextual response generation","Supabase-backed knowledge base lookup","Deepgram TTS to produce natural-sounding audio replies sent to Telegram"],"target_audience":["Businesses","Customer support teams","Content creators and podcasters focused on voice UX/UX accessibility teams"]}


name: Competitor Price Monitoring with Web Scraping,Google Sheets & Telegram
author_name: Tony Paul
author_username: tonydatahut
categories: []
created_at: 2025-06-04T03:40:59.974Z
updated_at: 2025-06-04T03:40:59.974Z
url: https://n8n.io/workflows/4640
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  How it works

  ++Download the google sheet here++ and replace this with the googles sheet node: Google sheet , upload to google sheets and replace in the google sheets node.

  Scheduled trigger: Runs once a day at 8 AM (server time).

  Fetch product list: Reads your “master” sheet (product_url + last known price) from Google Sheets.

  Loop with delay: Iterates over each row (product) one at a time, inserting a short pause (20 s) between HTTP requests to avoid blocking.

  Scrape current price: Loads each product_url, extracts the current price via a simple CSS selector.

  Compare & normalize: Compares the newly scraped price against the “last_price” from your sheet, calculates percentage change, and tags items where price_changed == true.

  On price change:
  Send alert: Formats a Telegram message (“Price Drop” or “Price Hike”) and pushes it to your configured chat.

  Log history: Appends a new row to a separate “price_tracking” tab with timestamp, old price, new price, and % change.

  Update master sheet: After a 1 min pause, writes the updated current_price back to your “master” sheet so future runs use it as the new baseline.

  Set up step
  Google Sheets credentials (~5 min)
  Create a Google Sheets OAuth credential in n8n. 
  Copy your sheet’s ID and ensure you have two tabs: 
  product_data (columns: product_url, price) 
  price_tracking (columns: timestamp, product_url, last_price, current_price, price_diff_pct, price_changed) 
  Paste the sheet ID into both Google Sheets nodes (“Read” and “Append/Update”). 
  Telegram credentials (~5 min) 
  Create a Telegram Bot token via BotFather. 
  Copy your chat_id (for your target group or personal chat). 
  Add those credentials to n8n and drop them into the “Telegram” node.

  Workflow parameters (~5 min)

  Verify the schedule in the Schedule Trigger node is set to 08:00 (or adjust to your preferred run time).

  In the Loop Over Items node, confirm “Batch Size” is 1 (to process one URL at a time).
   
  Adjust the Delay to avoid Request Blocking node if your site requires a longer pause (default is 20 s).
   
  In the Parse Data From The HTML Page node, double-check the CSS selector matches how prices appear on your target site.
   
  Once credentials are in place and your sheet tabs match the expected column names, the flow should be ready to activate. Total setup time is under 15 minutes—detailed notes are embedded as sticky comments throughout the workflow to help you tweak selectors, change timeouts, or adjust sheet names without digging into code.

nodes_used:
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workflow_json_compressed:
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metadata_json:
  {"categories":["automation","data processing","web scraping","monitoring","integration"],"complexity":"medium","use_cases":["Competitor price monitoring","Automated price-change alerts","Market / pricing research","E‑commerce price tracking","Historical price logging and analysis"],"estimated_setup_minutes":15,"required_services":["Google Sheets (Google Sheets API / OAuth credential)","Telegram Bot API (Bot token and chat_id)","Target websites/pages to scrape (HTTP access)","n8n instance (workflow runtime)"],"key_features":["Daily scheduled run (Schedule Trigger)","Reads product master list from Google Sheets","Serial scraping with delay to avoid blocking (splitInBatches + Delay)","Extracts price via CSS selector (HTML parse)","Compares and normalizes prices, computes % change and flags changes
  (If/Code nodes and normalization logic)"],"target_audience":["E‑commerce managers","Pricing analysts","Small business owners selling online products/services who monitor competitors' prices"]}


name: Summarize Calls & Notify Teams via HubSpot, Slack, Email, WhatsApp
author_name: Encoresky
author_username: encoresky
categories: []
created_at: 2025-06-04T08:02:04.432Z
updated_at: 2025-06-04T08:02:04.432Z
url: https://n8n.io/workflows/4641
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow automates the process of handling conversation transcriptions and distributing key information across your organization. Here's what it does:

  Trigger: The workflow is initiated via a webhook that receives a transcription (e.g., from a call or meeting).

  Summarization & Extraction: Using AI, the transcription is summarized, and key information is extracted — such as action items, departments involved, and client details.

  Department Notifications: The relevant summarized information is automatically routed to specific departments via email based on content classification.

  CRM Sync: The summarized version is saved to the associated contact or deal in HubSpot for future reference and visibility.

  *Multi-Channel Alerts: *The summary is also sent via WhatsApp and Slack to keep internal teams instantly informed, regardless of platform.

  Use Case:
  Ideal for sales, customer service, or operations teams who manage client conversations and want to ensure seamless cross-departmental communication, documentation, and follow-up.

  Apps Used:

  Webhook (Trigger)

  OpenAI (or other AI/NLP for summarization)

  HubSpot

  Email

  Slack

  WhatsApp (via Twilio or third-party provider)

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chainSummarization","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmailTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.hubspot","n8n-nodes-base.hubspot"]

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metadata_json:
  {"categories":["automation","CRM integration","communication","AI/NLP","notifications"],"complexity":"medium","use_cases":["Automated summarization of calls/meetings","Extracting action items and departments from conversations","Routing summaries to departments via email","Syncing conversation summaries to HubSpot contacts/deals","Sending multi-channel alerts (Slack, WhatsApp) for fast team awareness"],"estimated_setup_minutes":60,"required_services":["Webhook endpoint (to receive transcriptions)","OpenAI or other AI/NLP provider","HubSpot","Slack","Email provider (SMTP or transactional email service)","WhatsApp via Twilio or third‑party provider"],"key_features":["AI summarization of transcriptions","Extraction of action items, departments, and client details","Content classification to determine department routing","Automatic email notifications to relevant departments","Sync summarized notes to HubSpot contact or deal records"],"target_audience":["Sales teams","Customer success/support teams","Operations teams handling client conversations」「Revenue/sales operations and managers"]}


name: SSL Certificate Expiry Notifier (No Paid APIs)
author_name: Evoort Solutions
author_username: evoortsolutions
categories: []
created_at: 2025-06-04T09:49:31.793Z
updated_at: 2025-06-04T09:49:31.793Z
url: https://n8n.io/workflows/4643
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Great — here’s a complete Workflow Description for your n8n Creator submission based on the JSON you shared:

  🔒 SSL Expiry Notifier (No Paid APIs)

  🧩 How it Works

  This workflow automatically checks SSL certificate expiry dates for a list of websites and sends timely email alerts if any certificate is close to expiring. It’s ideal for DevOps, IT Operations, or Web Admin teams to stay ahead of certificate issues —
   without relying on any paid API services.

  Here's the high-level logic:

  Trigger: Runs daily at 8 AM using the Schedule Trigger node.
  Fetch URLs: Reads URLs to monitor from a Google Sheet.
  Check SSL: Calls the free ssl-checker.io API to retrieve SSL certificate details (valid from, valid till, days left).
  Conditional Check: Filters any certificates expiring in 7 days or less.
  Send Email: Sends a styled HTML email alert to predefined recipients.
  Update Sheet: Updates the same Google Sheet with the latest SSL info for each domain.

  ⚙️ Set Up Steps (Quick Overview)

  🕐 Estimated setup time: \~10–15 minutes

  Connect Google Sheets – OAuth2 credentials required. Sheet must include a column titled URL with domains to monitor.
  Set Up SMTP – Add your email credentials under the SMTP node to enable notifications.
  Optional – Customize the threshold days in the "Expiry Alert" IF node if you want alerts for a different timeframe.
  Deploy and Activate – That’s it. Once active, the flow runs automatically every day.

  💡 Detailed field mappings and logic notes are included inside the workflow as sticky notes.

  🚀 Ready to Get Started?

  Let’s start your journey on n8n by creating your free account here.  

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["monitoring","automation","integration","notifications","IT operations"],"complexity":"simple","use_cases":["Monitor SSL certificate expiry for multiple domains","Send automated email alerts for expiring certificates","Maintain an up-to-date record of certificate details in a Google Sheet","Avoid paid APIs by using free ssl-checker.io","Customizable alert threshold for proactive remediation"],"estimated_setup_minutes":15,"required_services":["n8n","Google Sheets (OAuth2)","SMTP server or email service credentials","ssl-checker.io (free API)"],"key_features":["Daily scheduled checks (Schedule Trigger)","Reads domain list from Google Sheets","Uses free ssl-checker.io to fetch certificate expiry details","Filters certificates expiring within a configurable threshold","Sends styled HTML email alerts to recipients via SMTP node or Communication node alternative if configured (no paid APIs required)"],"target_audience":["DevOps engineers","IT operations teams","Web administrators / site owners / SREs"]}


name: Create AI-Powered Website Chatbot with Langflow Backend and Custom Branding
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-06-04T10:02:44.761Z
updated_at: 2025-06-04T10:02:44.761Z
url: https://n8n.io/workflows/4645
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow integrates a chatbot frontend with a backend powered by Langflow, a visual low-code AI development tool. The flow is triggered whenever a chat message is received via the n8n chatbot widget embedded on a website. It then sends the message to a Langflow flow for processing and returns the generated response to the user.

  How It Works  
  Chat Trigger: The workflow starts with a webhook trigger (When chat message received) that listens for incoming chat messages from the n8n Chat interface.  
  Langflow Integration: The chat input is sent to a Langflow instance via an HTTP request (Langflow node). The request includes the user's message and expects a response from the Langflow flow.  
  Response Processing: The output from Langflow is extracted and formatted using the Edit Fields node, ensuring the chatbot displays the response correctly.  
  Customization: Sticky notes provide instructions for embedding the n8n Chat widget on a website and customizing its appearance, including welcome messages, language settings, and branding.  

  Set Up Steps  
  Configure Langflow Connection:  
     Replace LANGFLOW_URL and FLOW_ID in the HTTP request node with your Langflow instance details.  
     Ensure the API headers (e.g., Content-Type: application/json) and authentication (if required) are correctly set.  

  Deploy n8n Chat:  
     Add the provided CDN script to your website, replacing YOUR_PRODUCTION_WEBHOOK_URL with the webhook URL generated by the When chat message received node.  
     Customize the chatbot’s UI (e.g., title, placeholder text, initial messages) using the JavaScript snippet in the sticky notes.  

  Activate Workflow:  
     Toggle the workflow to "Active" in n8n.  
     Test the chatbot by sending a message and verifying the Langflow response is processed and displayed correctly.  

  Advantages

  ✅ Seamless Langflow Integration
  It allows n8n to communicate directly with a Langflow flow via API, enabling AI responses using custom-designed Langflow logic.

  ✅ No-Code Chatbot Deployment
  With just a script snippet, the chatbot widget can be embedded into any website. Minimal coding is required to launch a fully functioning AI chatbot.

  ✅ Customizable UI/UX
  The included embed code offers full control over the chatbot's appearance, language, welcome message, input placeholder, and branding—ideal for white-label or customer-facing deployments.

  ✅ Modular and Extensible
  Because it's built in n8n, this chatbot can be easily extended with other services like CRMs, email alerts, or databases, without leaving the platform.

  ✅ Real-Time AI Interactions
  Thanks to Langflow's API and chat response support, users get immediate and dynamic AI-driven replies.

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","ai/chatbot","web-deployment"],"complexity":"medium","use_cases":["Website AI chatbot for customer support and FAQs","Lead capture and qualification","White‑label/chatbot branding for products/sites","Real‑time AI-driven user interactions","Extendable workflows to CRM, DBs, or notifications"],"estimated_setup_minutes":30,"required_services":["Langflow instance with API access (FLOW_ID + endpoint)","n8n (workflow runtime with Chat widget and webhook)","Website or web host where you can embed the n8n Chat widget (or a CDN-served script)","Network access between n8n and Langflow (firewall/API access)"],"key_features":["Webhook trigger for incoming chat messages (n8n Chat widget)","Sends user input to Langflow via HTTP request and receives AI responses","Response extraction and formatting using Edit/Set nodes","Embeddable chatbot widget with customizable UI, welcome message, language and branding","No-code/low-code deployment — minimal scripting to embed and customize widget UI/UX','Modular — easy to extend with CRMs, databases, email alerts, analytics"],"target_audience":["Developers building AI chat experiences","Product managers and SaaS founders deploying site chatbots","Marketers and support teams wanting branded customer chatbots without heavy engineering effort\",\"No-code/low-code users and integrators"]}


name: Rank Math Bulk Title & Description Optimizer for WordPress
author_name: phil
author_username: phil
categories: []
created_at: 2025-06-04T10:29:55.157Z
updated_at: 2025-06-04T10:29:55.157Z
url: https://n8n.io/workflows/4646
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Bulk WordPress SEO Meta Optimizer with Rank Math & AI

  This n8n workflow, along with its companion WordPress plugin (rank_math_tools.zip), automates the bulk optimization of your WordPress posts' Rank Math SEO titles and descriptions using AI. 

  Stop manually crafting metas and let AI supercharge your SEO efforts efficiently!

  free version here.

  How it works:

  This workflow streamlines your SEO process through several automated steps:

  Fetches Post IDs:** Retrieves all published post IDs from your WordPress site using a secure, custom API endpoint provided by the companion plugin.
  Gathers Post Content:** For each identified post, it accesses the existing title, slug, and main rendered content to provide context for the AI.
  AI-Powered Meta Generation:** Leverages an AI model of your choice via OpenRouter (defaulting to Claude 3.7 Sonnet) to generate an optimized SEO title and meta description. This generation is guided by a detailed, customizable prompt within the "Create Meta Infos" node, allowing you to define the style, tone, and SEO strategy.
  Updates WordPress Metas:** Sends the newly generated SEO title and description back to your WordPress site via another custom API endpoint. The companion plugin then updates the specific Rank Math fields for each post.
  Refreshes Modified Date:** The companion plugin automatically updates the post's 'last modified' date in WordPress whenever meta information is changed, which can be a positive signal for search engines.
  Selective Processing:** An "IF" node ("Should I Rewrite") intelligently determines whether a post's metas need updating based on predefined conditions (e.g., empty metas or placeholder content), optimizing resource usage.

  Setup Steps:

  Get up and running in approximately 15-25 minutes by following these high-level steps. Detailed instructions are available in the comprehensive documentation provided with your purchase and within the sticky notes inside the n8n workflow itself.

  Install the Companion WordPress Plugin:
      Download the rank_math_tools.zip file.
      Upload and activate it on your WordPress site.
      (Estimated time: 2-5 minutes)
  Configure WordPress API Authentication:
      In your WordPress admin area, go to your user profile and create a new Application Password.
      Ensure the user has at least an "Editor" role.
      Copy the generated password.
      (Estimated time: 2-5 minutes)
  Set Up n8n Credentials:
      In n8n, create a new "WordPress API" credential using your WordPress username, the Application Password you just copied, and your site's Base URL.
      Create a new "OpenRouter Api" credential using your OpenRouter API key.
      (Estimated time: 5-10 minutes, assuming you have your OpenRouter key ready)
  Import and Configure the n8n Workflow:
      Download the Bulk_Wordpress_Meta_Data_Optimizer_Gumroad.json workflow file.
      Import it into your n8n instance.
      Link your newly created WordPress and OpenRouter credentials to the respective nodes in the workflow.
      Verify and update your WordPress site URL in the "settings" node (ensure it has a trailing slash /).
      Review the "Limit" node – it's pre-set to process only 5 items for safe initial testing.
      (Estimated time: 5-10 minutes)

  Benefits:

  Full SEO Meta Automation:** Drastically reduce manual effort by automatically generating and updating SEO titles and descriptions for all your posts.
  Bulk Processing Power:** Efficiently handle meta optimization for hundreds or thousands of WordPress posts.
  Highly Customizable AI Output:** Fine-tune the AI's generation style, keyword focus, and direct response techniques by editing the detailed prompt within the "Create Meta Infos" node.
  Improved SEO Consistency & Quality:** Ensure all your articles have relevant, compelling, and optimized meta tags, adhering to best practices.
  Signal Freshness to Search Engines:** The automatic update of the post 'last modified' date upon meta change can help improve crawl frequency and SEO.
  Resource-Efficient Updates:** The "Should I Rewrite" node prevents unnecessary processing and API calls for posts that already have satisfactory meta information.
  Save Time & Focus on Content:** Free up valuable time to concentrate on creating great content, rather than on repetitive SEO tasks.

  To understand exactly how to use and customize this workflow in detail, please refer to the comprehensive step-by-step documentation provided with your purchase.

  For professional n8n automation services for your business, contact:
  Phil | Inforeole

nodes_used:
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metadata_json:
  {"categories":["automation","integration","SEO","AI content generation","WordPress"],"complexity":"medium","use_cases":["Bulk-generate SEO titles and meta descriptions for WordPress posts","Improve SEO consistency and quality across a site","Refresh post modified dates when metas change to signal freshness","Selective rewriting to avoid unnecessary updates","Batch processing large numbers of posts with AI-guided output"],"estimated_setup_minutes":20,"required_services":["n8n instance","WordPress site (with Rank Math plugin recommended)","Companion WordPress plugin (rank_math_tools.zip) providing custom API endpoints","WordPress Application Password (for API authentication)","OpenRouter API (or compatible AI model endpoint, e.g., Claude 3.7 Sonnet)"],"key_features":["Fetches published post IDs via custom plugin API","Retrieves title, slug and rendered content for context","AI-powered generation of SEO title and meta description with customizable prompt","Updates Rank Math meta fields via companion plugin API","Automatic update of post's last modified date after meta change (via plugin) to signal freshness to search engines','Selective processing using an IF node to skip satisfactory metas','Batch/limit node for safe initial testing and scalable processing','Configurable model/credentials (OpenRouter) and WordPress credentials"],"target_audience":["WordPress site owners","SEO specialists and digital marketers","Content managers and editors handling large archives of posts」「Developers and automation engineers implementing n8n workflows"]}


name: Automate Gmail Labeling with Gemini AI & Build InfraNodus Knowledge Graph with Telegram Alerts
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-06-04T11:13:35.956Z
updated_at: 2025-06-04T11:13:35.956Z
url: https://n8n.io/workflows/4647
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Automated Gmail Labeling and Brainstorming

  This template can be used to automatically label your incoming Gmail messages with AI and to build a knowledge graph from the emails tagged with a specific label to brainstorm new ideas based on them.

  You can also get notified about the emails with the most important labels via Telegram as well as receive new ideas as you are building a knowledge graph of incoming messages.

  The idea generation is based on the InfraNodus knowledge graph content gap detection algorithm, which builds a network from your content and then finds a blind spot and uses AI to generate an interesting research question or idea that can be used to bridge this gap.

  Why it works so well?

  Think of all the business emails you receive that bypass the spam filters. Probably, they are personalized to you already. Now imagine if you build a knowledge graph from them for over a month. You will then have a ideation device based on your interests and marketing profile. Now, if you identify the gaps inside and generate interesting research questions based on them, you will come up with new interesting ideas that will be relevant (because they touch on the topics that matter to you), but novel, because they bridge them in new ways.

  What is it useful for?

  Automate Gmail incoming message labeling** with the new Classifier n8n node — much more advanced than the default Gmail labeling rules.
  Get notified via Telegram (or a messenger of your choice) about the most important messages and be sure not to miss anything important.
  Keep the messages with a certain label saved into knowledge graph for brainstorming and ideation. 
  Every time a new message of this category comes in, it's added into the graph, changing its structure, a new idea is generated. So instead of looking at each specific offer, you now use them to generate insights for you.

  How it works


  Step 1: This template can is triggered automatically when a new Gmail message arrives.
  Note: you need to connect your Gmail account here in this node

  Step 2: We use the new n8n AI Classifier Node to classify your email based on its content. You might need to update to n8n 1.94 version to make it work.
  Note: we like to use Gemini AI for that classifier as it's the same company as Gmail, so should be safe with data

  Step 3: After classifying the message, we label the message with the appropriate label. 
  Note: you need to create the labels before in your Gmail account

  Step 4: For a certain category (e.g. "Business" you format the message and save it into your InfraNodus graph. 
  *Note: specify your InfraNodus API here and choose the name of the graph. It will use the InfraNodus HTTP graphAndEntries endpoint and save your data to an InfraNodus graph. 
  By default, we save the text knowledge graph using the  contextSettings parameters (it will only build a text graph of the content), but you can take an alternative setting from this InfraNodus HTTP node's settings and create a social knowledge graph, that will also show email senders in the graph itself.*

  Step 5 (optional): Generate an interesting insight question with the graphAndAdvice endpoint) of InfraNodus. 

  Step 6 (optional): Then send this insight via Telegram to a chat.

  Step 7 (optional): Link some important labels to the second Telegram notification node, so you receive important messages for specified labels.


  Step 8 (optional): Send a Telegram notification 

  We use Telegram, because it takes only 30 seconds to set up a bot with an API (send /newbot to @botfather, unlike Discord or Slack, which is long and cumbersome to set up. You can also attach a Gmail send node and generate an email instead. 

  How to use

  You need an InfraNodus GraphRAG API account and key to use this workflow. 

  Create an InfraNodus account or log in.
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  Add this Authorization code in Steps 4 and 5 of the workflow.  
  Come up with the name of the graph and change it in the HTTP InfraNodus nodes in the steps 4 and 5 and also in the Telegram node in Step 6 that sends a link to the graph.
  For additional text processing / idea generation settings you can use in the HTTP InfraNodus nodes, see the InfraNodus access points page. For example, in Step 4 you can change the text processing settings to build a social knowledge graph (settings are available in the Node's Notes section) and in Step 5 you can change the requestMode from question to idea to receive business ideas instead.
  Authorize your Gmail account for Steps 2, 3, 7 and 8 Gmail nodes. The easiest way to set it up is to open a free Google Console API account and to create an OAuth access point for n8n. You can then reuse it with other Google services like Google Sheets, Drive, etc. So it's a useful thing to have in general.
  Set up the Gemini AI API key using the instructions in the Step 2 Gemini AI classification node.
  Set up the Telegram node bot for the Step 8. It takes only 30 seconds: just go to @botfather and type in /newbot and you'll have an API key ready. To get the conversation ID, follow the n8n / Telegram instructions in the node itself. 
  Once everything is ready, try to run the default automated workflow to test if everything works well. 

  Requirements

  An InfraNodus account and API key
  An Google Cloud API OAuth client and key for Gmail access
  A Gemini AI API key
  A Telegram bot API key
  n8n version 1.94 and higher (for Text Classification AI node to work)

  Customizing this workflow

  Check our other n8n workflows at https://n8n.io/creators/infranodus/ for useful content gap analysis, expert panel, and marketing, and research workflows that utilize GraphRAG for better AI generation.

  Finally, check out https://infranodus.com to learn more about our network analysis technology used to build knowledge graphs from text.

  For support, please, contact https://support.noduslabs.com

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name: Auto-Create Geotab Zone for New Salesforce Work Order
author_name: Sobek
author_username: maagic
categories: []
created_at: 2025-06-04T11:59:09.102Z
updated_at: 2025-06-04T11:59:09.102Z
url: https://n8n.io/workflows/4648
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  📝 DESCRIPTION OF THE WORKFLOW

  This workflow connects Salesforce and Geotab to streamline fleet tracking for field service jobs (Work Orders). When a new Work Order is created in Salesforce (with a 'New' status and valid coordinates), it creates a circular geofence zone in Geotab and updates the Work Order with the zone ID. If geolocation is missing, an alert email is sent to dedicated email.

  The workflow uses a Salesforce Outbound Message to trigger an n8n webhook. It includes robust credential handling and optional logic to skip or notify on bad data.

  Use Cases:

  Automating vehicle geofence setup for service visits
  Enhancing CRM-to-fleet system synchronisation
  Enforcing work orders data quality via alerts

  Integrations Used:

  Salesforce
  Geotab API
  Microsoft Outlook (or any SMTP-compatible service)

  Tags:
  geotab, salesforce, fleet management, gps tracking, field service, crm, automation, webhook, integration

  ADDITIONAL RESOURCES
  🔗 Salesforce

  Salesforce Login
  \[Salesforce Setup (Admin Console)]\(https://login.salesforce.com/ → click “Setup” gear icon)
  Outbound Messages Documentation
  Salesforce Developer Documentation
  Salesforce Workbench (API Testing Tool)

  🔗 Geotab

  Geotab Login (MyGeotab)
  Geotab Developer Portal
  Geotab API Explorer
  Geotab SDK (JavaScript Samples)
  Geotab Support Centre

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metadata_json:
  {"categories":["integration","automation","fleet management","data quality"],"complexity":"medium","use_cases":["Automatically create geofence zones in Geotab when new Salesforce Work Orders are created","Keep CRM work orders and fleet tracking systems synchronized","Notify operations or data stewards when work orders lack valid geolocation","Streamline field service setup for vehicle routing and job enforcement"],"estimated_setup_minutes":30,"required_services":["Salesforce (with Outbound Messages configured)","Geotab API / MyGeotab account","Email service (Microsoft Outlook or any SMTP-compatible provider)"],"key_features":["Salesforce Outbound Message -> n8n webhook trigger","Creates circular geofence zone in Geotab using provided coordinates","Updates Salesforce Work Order with created Geotab zone ID","Sends alert email when geolocation is missing or invalid","Credential handling and optional skip/notify logic for bad data"],"target_audience":["CRM administrators","Fleet managers / operations","Field service teams / dispatchers"]}


name: 📍 Daily Nearby Garage Sales Alerts via Telegram
author_name: Thibaud
author_username: tderouze
categories: []
created_at: 2025-06-04T12:36:14.228Z
updated_at: 2025-06-04T12:36:14.228Z
url: https://n8n.io/workflows/4649
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Get a personalized list of garage sales happening today, based on your current location, directly in Telegram each morning! This n8n workflow integrates Home Assistant and Brocabrac.frto:
  Automatically detect your location every day
  Scrape and parse garage sale listings from Brocabrac
  Filter for high-quality and nearby events
  Send a neatly formatted message to your Telegram account

  Perfect for treasure hunters and second-hand enthusiasts who want to stay in the loop with zero effort!

nodes_used:
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metadata_json:
  {"categories":["automation","integration","notifications","web-scraping","location-based"],"complexity":"medium","use_cases":["Daily alerts for nearby garage/yard sales","Automated local event discovery","Personalized marketplace monitoring","Reducing manual search for second-hand items"],"estimated_setup_minutes":30,"required_services":["Home Assistant","Brocabrac.fr (website scraping)","Telegram (bot/account)"],"key_features":["Automatic daily location detection via Home Assistant","Scrape and parse Brocabrac listings","Filter results by quality and proximity","Scheduled push message to Telegram with formatted summary","Configurable filters and scheduling"],"target_audience":["Second-hand enthusiasts and treasure hunters","Home Assistant users","Local shoppers looking for deals on garage sales and flea markets"]}


name: Clone LinkedIn Writing Styles with AI Analysis & Prompt Generation to Airtable
author_name: Badr
author_username: b4dr
categories: []
created_at: 2025-06-04T13:29:41.494Z
updated_at: 2025-06-04T13:29:41.494Z
url: https://n8n.io/workflows/4650
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Boost Your Content Speed & Grow Authority in Your LinkedIn Space 

  Are you tired of spending HOURS crafting the perfect LinkedIn posts? This revolutionary n8n workflow is changing the game for content creators, marketing agencies, and business leaders worldwide.

  WHAT MAKES THIS TOOL A GAME-CHANGER 

  The LinkedIn Style Extractor & Prompt Generator uses cutting-edge AI technology to analyze ANY LinkedIn profile, extract their unique writing fingerprint, and create custom AI prompts that perfectly replicate their style. Stop struggling with content creation - start publishing high-converting posts in minutes!

  PREMIUM FEATURES

  ✅ Advanced LinkedIn Profile Mining*: Extracts *ALL public posts from any LinkedIn profile with one click
  ✅ AI Style Recognition Technology**: Our proprietary algorithm detects unique writing patterns, emotional triggers, persuasion techniques, and engagement hooks that make their content viral
  ✅ Custom Prompt Engineering**: Creates pixel-perfect system prompts that force ANY AI to write exactly like your target influencer - their tone, structure, hooks, and signature style
  ✅ Seamless Airtable Integration**: Automatically organizes and saves all your generated prompts in your Airtable database for instant access

  THREE SIMPLE STEPS TO CONTENT MASTERY

  ENTER ANY LINKEDIN PROFILE - Just paste a URL or username into our simple form
  WAIT 60 SECONDS - Our AI engine analyzes hundreds of data points to extract the exact writing formula
  GET YOUR CUSTOM PROMPT - Use it with ChatGPT, Claude, or any AI to instantly create content that sounds exactly like them

  WHO NEEDS THIS TOOL? EVERYONE WHO WANTS TO WIN ON LINKEDIN! 

  Marketing Agencies**: Create client content 10X faster while maintaining their exact voice and style
  Business Owners**: Clone your top competitor's writing style and beat them at their own game
  Content Creators**: Analyze viral influencers in your niche and adapt their winning formulas
  LinkedIn Coaches**: Scale your content creation while maintaining your authentic voice
  Personal Brands**: Ensure consistent messaging across your entire content ecosystem

  EASY SETUP - READY IN MINUTES 

  You'll need:

  Apify account (free tier works for testing)
  OpenRouter account (for accessing premium AI models)
  Airtable account (free tier supports up to 1,200 prompt records!)

  SETUP IN UNDER 5 MINUTES 

  Import the workflow into your n8n instance with one click
  Connect your accounts with our guided setup wizard:
     Apify API Key
     OpenRouter API Key
     Airtable API Key
  Customize your storage with our pre-built Airtable template
  START EXTRACTING STYLES and creating viral content immediately!

  INSIDER TIPS FOR MAXIMUM ROI 

  Analyze Top Performers**: Target LinkedIn creators with high engagement rates (we recommend at least 10-15 posts)
  Master Multiple Styles**: Create a library of different writing styles for different content purposes

  Content Multiplier**: One style prompt can generate HUNDREDS of perfectly matched posts

  ADVANCED STRATEGY: Analyze profiles in your niche with the highest conversion rates (not just likes!)

  COMPLETELY ETHICAL & TOS-COMPLIANT 

  This workflow only accesses publicly available LinkedIn content. We've designed it to respect LinkedIn's Terms of Service while giving you the competitive edge you need. Use this powerful tool to ethically scale your content creation.

  Need a hand with automation? Let’s connect on X! 👉 https://x.com/TBR0007

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.airtable"]

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metadata_json:
  {"categories":["automation","integration","content creation","data extraction","AI/ML"],"complexity":"medium","use_cases":["Extract public LinkedIn posts for analysis","Automatically generate custom AI prompts that replicate a writer's style","Scale content creation for LinkedIn using generated prompts","Competitor or influencer style analysis for marketing strategy","Store and manage generated prompts in Airtable for reuse"],"estimated_setup_minutes":5,"required_services":["n8n instance","Apify (LinkedIn scraping)","OpenRouter (access to LLMs)","Airtable account","Public LinkedIn profiles (data source)"],"key_features":["Bulk extraction of public LinkedIn posts","AI-driven writing style recognition (tone, hooks, persuasion patterns)","Automated prompt engineering to replicate styles","Seamless Airtable integration to save/manage prompts","Quick one-click import and guided account setup in n8n"],"target_audience":["Content creators","Marketing agencies","Business owners and competitors analysis teams」「LinkedIn coaches」「Personal brands and social media managers"]}


name: Create a Branded AI Chatbot for Websites with Flowise Multi-Agent Chatflows
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-06-04T13:42:57.244Z
updated_at: 2025-06-04T13:42:57.244Z
url: https://n8n.io/workflows/4651
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow integrates Flowise Multi-Agent Chatflows into a custom-branded n8n chatbot, enabling real-time interaction between users and AI agents powered by large language models (LLMs).

  Key Advantages:

  ✅ Easy Integration with Flowise:

  Uses a low-code HTTP node to send user questions to Flowise's API (/api/v1/prediction/FLOWISE_ID) and receive intelligent responses.
  Supports multi-agent chatflows, allowing for complex, dynamic interactions.

  🎨 Customizable Chatbot UI:

  Includes pre-built JavaScript for embedding the n8n chatbot into any website.
  Provides customization options such as welcome messages, branding, placeholder text, chat modes (e.g., popup or embedded), and language support.

  🔐 Secure & Configurable:

  Authorization via Bearer token headers for Flowise API access.
  Clearly marked notes in the workflow for setting environment variables like FLOWISE_URL and FLOW_ID.

  How It Works  
  Chat Trigger: The workflow starts with the When chat message received node, which acts as a webhook to receive incoming chat messages from users.  
  HTTP Request to Flowise: The received message is forwarded to the Flowise node, which sends a POST request to a Flowise API endpoint (https://FLOWISEURL/api/v1/prediction/FLOWISE_ID). The request includes the user's input as a JSON payload ({"question": "{{ $json.chatInput }}"}) and uses HTTP header authentication (e.g., Authorization: Bearer FLOWSIE_API).  
  Response Handling: The response from Flowise is passed to the Edit Fields node, which maps the output ($json.text) for further processing or display.  

  Set Up Steps  
  Configure Flowise Integration:  
     Replace FLOWISEURL and FLOWISE_ID in the HTTP Request node with your Flowise instance URL and flow ID.  
     Ensure the Authorization header is set correctly in the credentials (e.g., Bearer FLOWSIE_API).  

  Embed n8n Chatbot:  
     Use the provided JavaScript snippet in the sticky notes to embed the n8n chatbot on your website. Replace YOUR_PRODUCTION_WEBHOOK_URL with the webhook URL generated by the When chat message received node.  
     Customize the chatbot's appearance and behavior (e.g., welcome messages, language, UI elements) using the createChat configuration options.  

  Optional Branding:  
     Adjust the sticky note examples to include branding details, such as custom messages, colors, or metadata for the chatbot.  

  Activate Workflow:  
     Toggle the workflow to "Active" in n8n and test the chat functionality end-to-end.  

  Ideal Use Cases:

  Embedding branded AI assistants into websites.
  Connecting Flowise-powered agents with customer support chatbots.
  Creating dynamic, smart conversational flows with LLMs via n8n automation.

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest"]

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metadata_json:
  {"categories":["automation","integration","chatbot","customer support","ai"],"complexity":"medium","use_cases":["Embed branded AI assistants on websites","Connect Flowise multi-agent chatflows to customer support chatbots","Create dynamic conversational flows with LLMs","Provide self-serve knowledge base / FAQ automation","Prototype conversational agents with custom UI"],"estimated_setup_minutes":30,"required_services":["Flowise instance (API access)","n8n instance (workflow host)","Publicly accessible webhook / website hosting for embedding chatbot (or ngrok)","LLM provider connected to Flowise (e.g., OpenAI, local model)"],"key_features":["Integrates Flowise multi-agent chatflows via HTTP POST","Pre-built JavaScript to embed customizable chatbot UI on websites","Bearer token authorization and environment variable configuration","Maps and edits Flowise responses for display in chat","Supports multiple chat modes (popup or embedded) and multilingual text/placeholder customization"],"target_audience":["Developers implementing website chatbots","Product owners and managers building branded assistants","Customer support teams automating responses with LLMs and chatflows','No-code/low-code automation builders"]}


name: AI Agent Creates Content to Be Picked by ChatGPT, Gemini, Google
author_name: Kritika
author_username: kritika-dagur
categories: []
created_at: 2025-06-04T15:38:35.056Z
updated_at: 2025-06-04T15:38:35.056Z
url: https://n8n.io/workflows/4652
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  🧠 Who is this for?
  Marketing teams, content creators, solopreneurs, and agencies who want to generate emotionally-resonant, SEO-optimized content tailored to audience psychology and buyer journey stages — and get picked up by AI discovery engines like ChatGPT, Gemini, and Perplexity.

  How it works: 
  ✅ Decodes why people buy (using buyer psychology)
  ✅ Creates SEO + emotionally resonant content for 4 formats:
  → Blog Posts, Newsletters, Landing Pages, Social Media
  ✅ Structures the content to be picked up by ChatGPT, Gemini, Perplexity & Google
  ✅ Automatically routes it to Google Sheets, Gmail, or even WordPress

  This isn’t just about writing better content — it’s about getting seen by the tools that shape the internet.

  How long does it take to set-up: 30 Mins 

nodes_used:
  ["n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.removeDuplicates","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.textClassifier","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.linkedIn","n8n-nodes-base.wordpress","n8n-nodes-base.wordpress","n8n-nodes-base.mailgun"]

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metadata_json:
  {"categories":["automation","content creation","marketing","SEO","integration"],"complexity":"medium","use_cases":["Generate SEO-optimized blog posts","Create newsletters and landing page copy","Produce social media content tailored to buyer journey stages","Optimize content for discovery by AI engines (ChatGPT, Gemini, Perplexity)","Automate routing to Google Sheets, Gmail, WordPress, LinkedIn"],"estimated_setup_minutes":30,"required_services":["Google Sheets","Gmail","WordPress","LinkedIn","ChatGPT / Gemini / Perplexity (LLM / discovery engines)","AI/ML provider (text generation & classification)"],"key_features":["Decodes buyer psychology to tailor messaging","Generates SEO + emotionally resonant content for blogs, newsletters, landing pages, social","Structures content for AI discovery engines","Automated routing to Google Sheets, Gmail, WordPress, LinkedIn","Duplicate removal and content classification steps (dedupe, text classifier)"],"target_audience":["Marketing teams","Content creators","Solopreneurs/founders/agencies involved in content and growth marketing"]}


name: LinkedIn Profile Extract and Build JSON Resume with Bright Data & Google Gemini
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-06-04T16:01:06.726Z
updated_at: 2025-06-04T16:01:06.726Z
url: https://n8n.io/workflows/4653
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who this is for?

  The LinkedIn Profile Extract and JSON Resume Builder is a powerful workflow that scrapes professional profile data from LinkedIn using Bright Data's infrastructure, then transforms that data into a clean, structured JSON resume using Google Gemini. The workflow is ideal for automating resume parsing, candidate profiling, or integrating into recruiting platforms.

  This workflow is tailored for:

  HR professionals & recruiters automating resume screening

  Talent acquisition platforms enriching candidate profiles

  Developers & AI builders creating resume-parsing AI pipelines

  Data scientists working on labor market analytics

  Growth hackers profiling prospects via public data

  What problem is this workflow solving?

  Parsing resumes or LinkedIn profiles into machine-readable formats is often a manual, error-prone process. Most scraping tools either fail due to anti-bot protections or return unstructured HTML that's hard to work with.

  This workflow solves that by:

  Using Bright Data's Web Unlocker for reliable, CAPTCHA-free LinkedIn scraping

  Extracting clean text and structured profile data via Google Gemini LLM

  Automatically generating a standards-compliant JSON Resume and Skills

  Sending the resume to webhooks or storing it for downstream usage

  What this workflow does

  Accepts LinkedIn Profile URL and required metadata (Bright Data zone, webhook)

  Scrapes LinkedIn profile using Bright Data Web Unlocker

  Extracts clean content and skills using Google Gemini LLM

  Builds a JSON-formatted resume following the JSON resume schema

  Sends the JSON resume via Webhook Notification

  Persists the output by saving the file to disk

  Setup

  Sign up at Bright Data.
  Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.
  In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication).

  The Value field should be set with the
  Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token.
  In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy).
  Update the Set URL and Bright Data Zone node with the LinkedIn profile, Bright Data Zone and the Webhook notification URL. For testing purposes, you can obtain a webhook url using https://webhook.site/

  How to customize this workflow to your needs

  Add Language Translation

  Insert a translation LLM node to support multilingual profiles.

  Generate PDF Resumes

  Convert JSON to formatted PDF resumes using an HTML-to-PDF module.

  Push to ATS or CRM

  Add integration nodes to pipe data into applicant tracking systems (ATS), CRMs, or databases.

  Use Alternative LLMs

  Swap Gemini with OpenAI or Anthropic Claude if preferred.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.informationExtractor","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.function","n8n-nodes-base.readWriteFile","n8n-nodes-base.httpRequest","n8n-nodes-base.readWriteFile","n8n-nodes-base.function","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.informationExtractor","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code"]

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metadata_json:
  {"categories":["data extraction","automation","integration","AI/LLM","recruiting"],"complexity":"complex","use_cases":["Automated resume parsing from LinkedIn","Candidate profiling and enrichment","Feeding structured resumes into ATS/CRM","Building machine-readable JSON resumes for analytics","Extracting skills and professional data for pipelines"],"estimated_setup_minutes":45,"required_services":["Bright Data Web Unlocker (proxy/zone and token)","Google Gemini (PaLM) API or Vertex AI access","n8n workflow runtime (with read/write file capability)","Webhook endpoint (e.g., webhook.site or your webhook receiver)","Filesystem or storage for persisting output"],"key_features":["CAPTCHA-free LinkedIn scraping via Bright Data Web Unlocker","LLM-based extraction and normalization using Google Gemini","Generates standards-compliant JSON Resume schema output","Skill extraction and structured profile fields","Sends JSON resume to webhooks and saves to disk for downstream use or integration"],"target_audience":["HR professionals and recruiters","Talent acquisition platforms","Developers and AI builders creating resume pipelines\",\"Data scientists doing labor market analytics\",\"Growth hackers/prospecting teams"]}


name: Daily Insight Email from Structured Web Data with Firecrawl
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-06-04T16:14:11.652Z
updated_at: 2025-06-04T16:14:11.652Z
url: https://n8n.io/workflows/4654
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  🔥 Daily Web Scraper & AI Summary with Firecrawl + Email Automation
  Need to extract and summarize web content from a site that doesn’t have an API? This workflow runs daily to scrape a web page using Firecrawl, summarize the content with OpenAI, and send it directly to your email — fully automated.

  Watch Full Video Step-by-step Tutorial Here:
  https://www.youtube.com/@Automatewithmarc

  🔧 How It Works
  Daily Trigger – Starts the workflow every 24 hours.

  Firecrawl Node – Crawls and extracts structured data from any web page you specify.

  OpenAI Node (Optional) – Processes and summarizes the raw content using a prompt you control.

  Gmail Node – Sends the final summary or content snapshot to your email inbox.

  ✅ Perfect For
  Business analysts tracking daily market or industry news

  Researchers and founders automating competitive intelligence

  Anyone who wants web data delivered without coding or scraping scripts

  🪜 Setup Instructions
  Firecrawl API Key – Sign up and insert your key in the credentials.

  Update Target URL – Edit the URL in the Firecrawl node to your desired site.

  Customize the Prompt – Tailor the OpenAI prompt to extract the insights you want.

  Connect Gmail – Add your Gmail credentials and set your recipient email.

  🧰 Built With
  Firecrawl (Web scraping without code)

  OpenAI (For summarizing and insight extraction)

  Gmail (Automated notifications)

  n8n (Workflow automation engine)

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.gmail","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","web scraping","data processing","notifications","AI/ML"],"complexity":"medium","use_cases":["Daily market or industry news aggregation","Competitive intelligence monitoring","Research updates and literature tracking","Automated content summarization and delivery","Non‑developer web data extraction without coding"],"estimated_setup_minutes":15,"required_services":["n8n","Firecrawl (API key)","OpenAI (optional, for summaries)","Gmail (or other email provider credentials)"],"key_features":["Scheduled (daily) trigger","No-code structured web scraping via Firecrawl","Optional AI summarization with OpenAI prompts","Automated email delivery of summaries via Gmail","Customizable target URL and prompt for tailored insights"],"target_audience":["Business analysts","Researchers","Founders / competitive intelligence teams"]}


name: Automated Invoice Management with Nextcloud, Email and Telegram Notifications
author_name: Joachim Hummel
author_username: jhummel
categories: []
created_at: 2025-06-04T16:20:01.278Z
updated_at: 2025-06-04T16:20:01.278Z
url: https://n8n.io/workflows/4655
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow automatically fetches PDF invoices from a Nextcloud folder (/Invoice/Incoming), sends them via email to a fixed recipient (invoice@example.com), sends a Telegram notification, and archives the file to /Invoice/2025/archive.

  Key Steps:
  Triggered daily at 8 AM
  Lists files in /Invoice/Incoming
  Filters for existing entries
  Downloads the file
  Sends the invoice via email
  Sends a Telegram message with filename
  Moves the file to archive

  📦 Technologies used:
  Nextcloud
  SMTP Email
  Telegram Bot

  ⚙️ Use case:
  Perfect for freelancers or small businesses to automate recurring invoice sending with minimal effort.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.nextCloud","n8n-nodes-base.if","n8n-nodes-base.nextCloud","n8n-nodes-base.emailSend","n8n-nodes-base.nextCloud","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["automation","integration","file management","notifications"],"complexity":"simple","use_cases":["Automatically send incoming invoices to an accountant or client","Archive processed invoices to a dated folder","Notify team/member when a new invoice is sent","Reduce manual invoice handling for freelancers or small businesses"],"estimated_setup_minutes":25,"required_services":["Nextcloud","SMTP email (any mail provider)","Telegram Bot API"],"key_features":["Daily scheduled trigger (8 AM)","List and filter files in Nextcloud folder","Download invoice PDFs and send as email attachments","Send Telegram notification with filename","Move processed files to archive folder"],"target_audience":["freelancers","small businesses","bookkeepers/accountants', 'operations teams"]}


name: Automate Instagram Content Discovery & Repurposing w/ Apify, GPT-4o & Perplexity
author_name: Nick Saraev
author_username: nicksaraev
categories: []
created_at: 2025-06-04T17:08:01.951Z
updated_at: 2025-06-04T17:08:01.951Z
url: https://n8n.io/workflows/4658
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  This workflow creates an end-to-end Instagram content pipeline that automatically discovers trending content from competitor channels, extracts valuable insights, and generates new high-quality scripts for your own content creation. The system helped scale an Instagram channel from 0 to 10,000 followers in just 15 days through intelligent content repurposing.

  Benefits:

  Complete Content Automation - Monitors competitor Instagram accounts, downloads new reels, and processes them without manual intervention
  AI-Powered Script Generation - Uses ChatGPT and Perplexity to analyze content, identify tools/technologies, and rewrite scripts with fresh angles
  Smart Duplicate Prevention - Automatically tracks processed content in a database to avoid redundant work
  Multi-Platform Intelligence - Combines Instagram scraping, AI transcription, web research, and content generation in one seamless flow
  Scalable Content Strategy - Process content from multiple niches and creators to fuel unlimited content ideas
  Revenue-Focused Approach - Specifically designed to identify monetizable tools and technologies for business-focused content

  How It Works:

  Instagram Content Discovery:
  Uses Apify's Instagram scraper to monitor specified creator accounts for new reels
  Automatically downloads video content and metadata from target accounts
  Filters content based on engagement metrics and relevance

  Intelligent Processing Pipeline:

  Transcribes video content using OpenAI Whisper for accurate text extraction
  Filters content using AI to identify tools, technologies, and automation opportunities
  Cross-references against existing database to prevent duplicate processing

  Enhanced Research & Analysis:

  Searches Perplexity AI for additional insights about discovered tools
  Generates step-by-step usage guides and implementation instructions
  Identifies unique angles and opportunities for content improvement

  Script Generation & Optimization:

  Creates new, original scripts optimized for your specific audience
  Maintains consistent brand voice while adding fresh perspectives
  Includes strategic call-to-action elements for audience engagement

  Required Google Sheets Database Setup:
  Before running this workflow, create a Google Sheets database with these exact column headers:
  Essential Columns:

  id - Unique Instagram post identifier (primary key for duplicate detection)
  timestamp - When the reel was posted
  caption - Original reel caption text
  hashtags - Hashtags used in the post
  videoUrl - Direct link to download the video file
  username - Account that posted the reel
  scrapedTranscript - Original transcript from video (added by workflow)
  newTranscript - AI-generated script for your content (added by workflow)

  Additional Tracking Columns:

  shortCode - Instagram's internal post code
  url - Public Instagram post URL
  commentsCount - Number of comments
  firstComment - Top comment on the post
  likesCount - Number of likes
  videoViewCount - View count metrics
  videoDuration - Length of video in seconds

  Setup Instructions:

  Create a new Google Sheet with these column headers in the first row
  Name the sheet "Reels"
  Connect your Google Sheets OAuth credentials in n8n
  Update the document ID in the workflow nodes

  The merge logic relies on the id column to prevent duplicate processing, so this structure is essential for the workflow to function correctly.


  Business Use Cases:

  Content Creators - Scale content production by 10x while maintaining quality and originality
  Marketing Agencies - Offer content research and ideation as a premium service
  Course Creators - Identify trending tools and technologies for educational content

  Revenue Potential:

  This exact system can be sold as a service for $3,000-$5,000 to growing channels or agencies. The automation saves 10+ hours weekly of manual research and content planning.

  Difficulty Level: Intermediate
  Estimated Build Time: 1-2 hours
  Monthly Operating Cost: ~$30 (API usage)

  Watch the Complete Build Process

  Want to see exactly how this system was built from scratch? Nick Saraev walks through the entire development process in this comprehensive tutorial, including all the debugging, dead ends, and problem-solving that goes into building real automation systems.

  🎥 Watch: "The N8N Instagram Parasite System (10K Followers In 15 Days)"


  This 1.5-hour deep-dive shows the actual build process - not a polished demo, but real system development with all the thinking and iteration included.

  Set Up Steps:

  Configure Apify Integration:

  Sign up for Apify account and obtain API key
  Replace the bearer token in the "Run Actor Synchronously" node
  Customize the username array with your target Instagram accounts

  Set Up AI Services:

  Add OpenAI API credentials for transcription and content generation
  Configure Perplexity API for enhanced research capabilities
  Set up appropriate rate limiting for cost control
  Database Configuration:

  Create Google Sheets database with provided column structure
  Connect Google Sheets OAuth credentials
  Configure the merge logic for duplicate detection

  Content Filtering Setup:

  Customize the AI prompts for your specific niche and requirements
  Adjust the filtering criteria for tool/technology detection
  Set up the script generation template to match your brand voice

  Automation Schedule:

  Configure the schedule trigger for daily content monitoring
  Set optimal timing based on your content creation workflow
  Test the complete flow with a small number of accounts first

  Advanced Customization:

  Add additional content sources beyond Instagram
  Integrate with your existing content management systems
  Scale up monitoring to dozens of competitor accounts

  More AI Automation Systems:*
  For more advanced automation tutorials and business systems, check out My YouTube Channel  where I share proven automation strategies that generate real revenue.

nodes_used:
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metadata_json:
  {"categories":["automation","social media","content creation","AI-driven research","data integration"],"complexity":"medium","use_cases":["Competitor Instagram monitoring and reel discovery","Automated video transcription and analysis","AI-powered script generation and content repurposing","Research enrichment (Perplexity) to identify tools/technologies","Duplicate detection and tracking via Google Sheets"],"estimated_setup_minutes":90,"required_services":["n8n","Apify (Instagram scraper)","OpenAI (Whisper transcription, GPT-4o/chat generation)","Perplexity API","Google Sheets (OAuth)"],"key_features":["Auto-discover and download reels from target accounts","Transcribe videos with Whisper","AI filter to identify tools/technologies and monetizable angles","Cross-reference and dedupe using Google Sheets id column","Augment research via Perplexity and generate step-by-step guides/insights"],"target_audience":["Content creators","Marketing agencies","Social media managers/growth teams`,`Course creators"]}


name: Forex News & Sentiment Telegram Alerts
author_name: Malik Hashir
author_username: malikx
categories: []
created_at: 2025-06-04T17:29:02.034Z
updated_at: 2025-06-04T17:29:02.034Z
url: https://n8n.io/workflows/4659
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Purpose & Audience

  This n8n workflow template is designed for Forex traders, analysts, and enthusiasts who want to automate the process of staying updated on the latest news and sentiment for any currency pair. By leveraging advanced news aggregation and sentiment analysis, the workflow delivers concise, actionable updates directly to your Telegram—helping you make more informed trading decisions without manual research on news for broader market sentiment.

  What It Does?
  Aggregates the latest news from major Forex platforms for your chosen currency pair.
  Analyzes the news to extract market sentiment (bullish, bearish, or neutral) using an LLM.
  Summarizes key headlines, technical levels (support/resistance), and highlights high-impact economic events.
  Sends a neatly formatted update to your selected Telegram chat or group at your preferred schedule.

  Who Is It For?
  Forex traders seeking a competitive edge by staying ahead of market sentiment shifts.
  Analysts who want automated, unbiased news curation and sentiment summaries.
  Anyone looking for a hands-off, plug-and-play solution to monitor any currency pair.

  Setup once, and you can use this workflow for a lifetime. Simply duplicate the workflow for as many currency pairs as you want—customize the inputs, and you’re set! No recurring fees, no coding required, and you control the update frequency and destinations.

  How to Set Up?
  Choose your currency pair and set your preferred update schedule.
  Connect your LLM and Telegram credentials (simple, guided steps included).
  Specify where you want to receive the updates.
  That’s it—receive real-time, actionable Forex news and sentiment updates automatically.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.merge","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.filter","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","data processing","trading","monitoring"],"complexity":"medium","use_cases":["Automated Forex news aggregation","Market sentiment monitoring for currency pairs","Scheduled Telegram alerts with summaries","Quick research and trade decision support","Monitoring high‑impact economic events"],"estimated_setup_minutes":20,"required_services":["LLM (Google Gemini / lmChatGoogleGemini)","Telegram account / bot credentials","Forex news RSS feeds or news APIs (e.g., ForexFactory, Investing.com, major news outlets)","(Optional) Economic calendar API or data source"],"key_features":["Aggregates latest Forex news for chosen currency pair","LLM-based sentiment analysis (bullish/bearish/neutral)","Concise summaries of headlines and key points","Extracts technical levels (support/resistance) and highlights high‑impact events","Scheduled delivery to Telegram chats/groups','Configurable currency pair and update frequency','Duplicate workflow per currency pair for multi‑pair monitoring"],"target_audience":["Forex traders","Market analysts","Trading enthusiasts and hobbyists who want automation without coding"]}


name: Enrich Company Data from LinkedIn via Bright Data & Google Sheets
author_name: Gleb D
author_username: glebd
categories: []
created_at: 2025-06-04T19:50:41.467Z
updated_at: 2025-06-04T19:50:41.467Z
url: https://n8n.io/workflows/4663
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n workflow automates the enrichment of a company list by discovering and extracting each company’s official LinkedIn URL using Bright Data’s search capabilities and Google Gemini AI for HTML parsing and result interpretation.

  Who is this template for?
  This workflow is ideal for sales, business development, and data research professionals who need to collect official LinkedIn company profiles for multiple organizations, starting from a list of company names in Google Sheets. It’s especially useful for teams who want to automate sourcing LinkedIn URLs, enrich their prospect database, or validate company data at scale.

  How it works
  Manual Trigger:
  The workflow is started manually (useful for controlled batch runs and testing).
  Read Company Names:
  Company names are loaded from a specified Google Sheets table.
  Loop Over Each Company:
  Each company is processed one-by-one:
  A custom Google Search URL is generated for each name.
  A Bright Data Web Unlocker request is sent to fetch Google search results for “site:linkedin.com [company name]”.
  Parse LinkedIn Profile URL Using AI:
  Google Gemini (or your specified LLM) analyzes the fetched search page and extracts the most likely official LinkedIn company profile.

  Result Handling:
  If a profile is found, it’s stored in the results.
  If not, an empty result is created, but you can add custom logic (notifications, retries, etc.).

  Batch Data Enrichment:
  All found company URLs are bundled into a single request for further enrichment from a Bright Data dataset.
  Export:
  The workflow appends the final, structured data for each company to another sheet in your Google Sheets file.
  Setup instructions
  1. Replace API Keys:
  Insert your Bright Data API key in these nodes:
  Bright Data Web Request - Google Search for Company LinkedIn URL
  HTTP Request - Post API call to Bright Data
  Snapshot Progress
  HTTP Request - Getting data from Bright Data

  2. Connect Google Sheets:
  Set up your Google Sheets credentials and specify the sheet for reading input and writing output.

  3. Customize Output Structure:
  Adjust the Python code node (see sticky note in the template) if you want to include additional or fewer fields in your output.

  4. Adjust for Scale or Error Handling:
  You can modify the logic for “not found” results (e.g., to notify a Slack channel or retry failed companies).

  5. Run the Workflow:
  Start manually, monitor the run, and check your Google Sheet for results.

  Customization guidance
  Change Input/Output Sheets:
  Update the sheet names or columns if your source/target spreadsheet has a different structure.

  Use Another AI Model:
  Replace the Google Gemini node with another LLM node if preferred.

  Integrate Alerts:
  Add Slack or email nodes to notify your team when a LinkedIn profile is not found or when the process is complete.

nodes_used:
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metadata_json:
  {"categories":["data enrichment","integration","automation"],"complexity":"medium","use_cases":["Automatically find official LinkedIn company profiles from a list of company names","Enrich prospect or CRM data with verified LinkedIn URLs","Validate and normalize company contact lists at scale","Batch enrichment using Bright Data datasets after URL discovery"],"estimated_setup_minutes":30,"required_services":["Bright Data (Web Unlocker / Datasets API)","Google Sheets (Google account / credentials)","Google Gemini (or other LLM for HTML parsing)"],"key_features":["Reads company names from Google Sheets","Generates Google search queries and fetches results via Bright Data","Uses an LLM to parse fetched HTML and extract the most likely LinkedIn company URL","Batches discovered URLs for further Bright Data dataset enrichment","Writes final structured results back to Google Sheets','Supports custom handling for \"not found\" results (notifications, retries)"],"target_audience":["Sales teams","Business development professionals","Data researchers and enrichment teams"]}


name: Automate Service Ticket Triage with GPT-4o & Taiga
author_name: Eric Mooney
author_username: emooney
categories: []
created_at: 2025-06-04T21:19:13.071Z
updated_at: 2025-06-04T21:19:13.071Z
url: https://n8n.io/workflows/4665
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Usecase: When a new service ticket is created in Taiga, it's often unclear whether it contains sufficient details to begin work. This workflow automates the triage process by:

  Using an AI model to extract key information from the ticket description.
  Automatically assigning values for:
     Type (Bug, Enhancement, Onboarding, Question)
     Severity (Wishlist, Minor, Normal, Important, Critical)
     Priority (Low, Normal, High)
     Status (New, Needs More Info, etc.)
  Detecting missing critical data and blocking the ticket if incomplete.

  Setup instructions here:
  https://github.com/emooney/Service_Ticket_Triage_Helper

nodes_used:
  ["n8n-nodes-base.taigaTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.taiga","n8n-nodes-base.switch","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.switch","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.switch","n8n-nodes-base.taiga","n8n-nodes-base.taiga","n8n-nodes-base.taiga","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

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metadata_json:
  {"categories":["automation","integration","AI-assisted triage","ticketing","workflow management"],"complexity":"complex","use_cases":["Automated service ticket triage","Extracting structured data from free-text ticket descriptions","Automatic assignment of ticket Type/Severity/Priority/Status","Detecting and blocking incomplete tickets","Improving ticket quality and team throughput"],"estimated_setup_minutes":45,"required_services":["Taiga (project management / ticket source)","OpenAI (GPT-4o / lmChatOpenAi)","n8n (workflow runner)","GitHub (optional - setup instructions repository)"],"key_features":["AI extraction of key information from ticket descriptions","Auto-assignment of Type, Severity, Priority, and Status","Detection of missing critical data and blocking incomplete tickets","Structured output parsing (outputParserStructured)","Conditional logic and routing (switch, if) for triage decisions and workflows"],"target_audience":["Support and Helpdesk teams","Product managers and engineering leads","DevOps / Site Reliability teams doing incident triage`,`n8n workflow builders and automation engineers"]}


name: Create Smart URLs with BioURL.link's Geo, Device & Language Targeting
author_name: Naser Emad
author_username: nasermetani
nodes_used: ["n8n-nodes-base.httpRequest","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook"]
categories: []
created_at: 2025-06-04T22:54:23.250Z
updated_at: 2025-06-04T22:54:23.250Z
url: https://n8n.io/workflows/4667
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Create sophisticated shortened URLs with advanced targeting and tracking capabilities using the BioURL.link API

  Overview
  This n8n workflow provides a powerful webhook-based URL shortening service that integrates with BioURL.link's comprehensive link management platform. Transform any long URL into a smart, trackable short link with advanced targeting features through a simple HTTP POST request.

  Key Features
  Smart URL Shortening**: Create custom short URLs with optional passwords and expiry dates
  Geo-targeting**: Redirect users to different URLs based on their geographic location
  Device Targeting**: Serve different content to iPhone, Android, or other device users  
  Language Targeting**: Customize redirects based on user language preferences
  Deep Linking**: Automatically redirect mobile users to app store or native apps
  Custom Meta Tags**: Set custom titles, descriptions, and images for social media sharing
  Analytics & Tracking**: Integrate tracking pixels and campaign parameters
  Splash Pages**: Create branded landing pages before redirects

  How It Works
  Webhook Trigger: Send a POST request to the /shorten-link endpoint
  API Integration: Workflow processes the request and calls BioURL.link's API
  Response: Returns the shortened URL with all configured features

  Setup Requirements
  BioURL.link account and API key
  Replace "Bearer YOURAPIKEY" in the HTTP Request node with your actual API key
  Customize the JSON body parameters as needed for your use case

  Use Cases
  Marketing campaigns with geo-specific landing pages
  Mobile app promotion with automatic app store redirects
  A/B testing with device or language-based targeting
  Social media sharing with custom preview metadata
  Time-sensitive promotions with expiry dates
  Password-protected internal links

  Technical Details
  Trigger**: Webhook (POST to /shorten-link)
  API Endpoint**: https://biourl.link/api/url/add
  Response**: Complete shortened URL data
  Authentication**: Bearer token required

  Perfect for marketers, developers, and businesses needing advanced URL management capabilities beyond basic shortening services.

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metadata_json:
  {"categories":["automation","integration","marketing","link management"],"complexity":"medium","use_cases":["Geo-specific marketing landing pages","Mobile app promotion with automatic app store redirects","A/B testing by device or language","Social media sharing with custom preview metadata","Time-sensitive promotions with expiry dates and passwords"],"estimated_setup_minutes":15,"required_services":["BioURL.link API (account + API key)"],"key_features":["Smart URL shortening with custom slugs","Geo-targeting redirects","Device-based targeting (iPhone, Android, others)","Language-based redirects","Deep linking to apps or app stores (mobile)"],"target_audience":["marketers","developers","growth/analytics teams`,`businesses needing advanced link management"]}


name: Extract Website URLs from Sitemap.XML for SEO Analysis
author_name: Le Thua Phu
author_username: lethuaphu
categories: []
created_at: 2025-06-05T03:47:49.851Z
updated_at: 2025-06-05T03:47:49.851Z
url: https://n8n.io/workflows/4671
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Overview
  This n8n workflow automates the process of crawling a website's sitemap to extract URLs, which is particularly useful for SEO analysis, website auditing, or content monitoring. By leveraging n8n's nodes, the workflow fetches the sitemap from a specified URL, processes the XML data, and extracts individual URLs, which can then be converted into a downloadable file or integrated with tools like Google Sheets.

  How It Works
  The workflow operates in a sequential manner, utilizing a series of nodes to fetch, parse, and process sitemap data:
  Trigger: Initiates when the user clicks "Test workflow" (Manual Trigger node).
  Set URL: Defines the base domain (e.g., https://phu.io.vn/) for the sitemap (Set URL node).
  Crawl Sitemap: Fetches the main sitemap file (sitemap.xml) from the specified domain using an HTTP request (Crawl sitemap node).
  Parse XML: Converts the sitemap XML into a JSON format for easier processing (XML node).
  Split Sitemap: Extracts individual sitemap entries (e.g., &lt;sitemap&gt; tags) from the parsed data (Split Out node).
  Crawl Sub-Sitemap: Fetches each sub-sitemap URL listed in the main sitemap (Crawl sitemap 2 node).
  Parse Sub-Sitemap XML: Converts the sub-sitemap XML into JSON (XML 2 node).
  Split URLs: Extracts individual URLs (e.g., &lt;url&gt; tags) from the sub-sitemap (Split Out 2 node).
  Convert to File: Saves the extracted URLs into a file for download or further use (Convert to File node).

  This workflow supports both single sitemap files and sitemap indexes that reference multiple sub-sitemaps, ensuring comprehensive URL extraction.

  How to Use
  To implement this workflow in n8n, follow these steps:
  Set Up n8n: Ensure you have an active n8n instance (Cloud, npm, or self-hosted). Refer to the n8n documentation for setup instructions.
  Import Workflow: Copy the JSON from the provided Extract Website URLs from Sitemap.XML for SEO Analysis.json file and import it into your n8n instance via the workflow editor.
  Configure the Domain:
     In the Set URL node, update the Domain parameter with the target website's base URL (e.g., https://example.com/).
     Alternatively, in the Crawl sitemap node, directly paste the full sitemap URL if known (e.g., https://example.com/sitemap.xml).
  Test the Workflow:
     Click "Test workflow" to execute the Manual Trigger node.
     Verify that the workflow fetches the sitemap and processes the URLs correctly.
  Download or Integrate:
     The Convert to File node generates a file containing the extracted URLs.
     Optionally, replace this node with a Google Sheets node to append URLs to a spreadsheet. Refer to the Google Sheets node documentation for setup.
  Save and Activate: Save the workflow and activate it for production use if needed, using a trigger like a schedule or webhook (see Trigger Node).

  Requirements
  n8n Instance**: An active n8n instance (version 1.0 or later recommended) on n8n Cloud, npm, or self-hosted (Docker). See Choose your n8n for details.
  Technical Knowledge**: Basic understanding of n8n's editor UI and node configuration. Familiarity with XML sitemaps is helpful but not mandatory.
  Permissions**: For self-hosted setups, ensure the n8n process has network access to fetch the sitemap URL. For Docker deployments, verify permissions as outlined in the n8n v1.0 migration guide.
  Optional**: If integrating with Google Sheets, valid Google Sheets credentials are required (see Credentials).
  Timeout Configuration**: The HTTP Request nodes (Crawl sitemap and Crawl sitemap 2) have a 10-second timeout. Adjust the timeout parameter in the node settings if dealing with slow-responding servers.

  FAQ
  Q: What happens if the sitemap is large or contains many sub-sitemaps?  
  A: The workflow handles sitemap indexes by splitting and processing each sub-sitemap individually. For very large sitemaps, ensure your n8n instance has sufficient resources (memory and CPU) to avoid performance issues. See Scaling n8n for optimization tips.

  Q: Can I use this workflow with a specific sitemap URL instead of a domain?  
  A: Yes, in the Crawl sitemap node, replace the url parameter ({{ $json.Domain }}sitemap.xml) with the direct sitemap URL (e.g., https://example.com/sitemap.xml). Update the node’s notes for clarity.

  Q: Why am I getting a timeout error?  
  A: The HTTP Request nodes have a default timeout of 10 seconds. If the target server is slow, increase the timeout value in the options parameter of the Crawl sitemap or Crawl sitemap 2 nodes.

  Q: How can I save the URLs to Google Sheets instead of a file?  
  A: Replace the Convert to File node with a Google Sheets node. Configure it with your Google Sheets credentials and map the loc field from the Split Out 2 node to the desired spreadsheet column. Refer to the Google Sheets node documentation.

  Q: Is this workflow compatible with older n8n versions?  
  A: The workflow uses nodes compatible with n8n version 1.0 and later. For older versions, check for deprecated features (e.g., MySQL support) in the n8n v1.0 migration guide.

  Q: Can I automate this workflow to run periodically?  
  A: Yes, replace the Manual Trigger node with a Schedule Trigger node to run the workflow at set intervals. See Trigger Nodes for configuration details.

  For further assistance, consult the n8n Community Forum or submit an issue on the n8n GitHub repository.

  Need help customizing?
  Contact me for consulting and support or add me on Facebook or email.

nodes_used:
  ["n8n-nodes-base.xml","n8n-nodes-base.manualTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.xml","n8n-nodes-base.splitOut","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","data processing","integration","SEO"],"complexity":"medium","use_cases":["Extract all URLs from a website sitemap for SEO audits","Crawl sitemap indexes and sub-sitemaps","Populate a list/file of site URLs for content monitoring or migration","Export URLs to Google Sheets or a downloadable file","Periodic sitemap checks via a scheduled trigger"],"estimated_setup_minutes":15,"required_services":["n8n instance (Cloud, npm or self-hosted)","Target website sitemap accessible over HTTP/HTTPS","Google Sheets API (optional, for spreadsheet integration)","Internet/network access from the n8n host"],"key_features":["Fetches sitemap.xml and any referenced sub-sitemaps","Parses XML to JSON for easy processing","Splits sitemap and URL entries to extract individual loc values","Handles both single sitemaps and sitemap indexes","Converts extracted URLs to a downloadable file or maps to Google Sheets (optional)"],"target_audience":["SEO specialists","Webmasters/site owners","Digital marketers and content managers who audit sites for SEO or migration workdflows, developers/automation engineers"]}


name: Voice Creation, TTS, Sound Effects, Voicechanger & more! 🎧 Elevenlabs MCP Server
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-05T04:18:44.626Z
updated_at: 2025-06-05T04:18:44.626Z
url: https://n8n.io/workflows/4672
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  This workflow provides a complete set of tools for interacting with the ElevenLabs voice API, enabling AI-powered text-to-speech, voice management, and audio processing capabilities.

  Features 🚀

  Text-to-Speech Operations
  Convert text to speech with customizable voice settings
  Generate speech with timestamps for precise audio control
  Stream text-to-speech in real-time
  Stream text-to-speech with timestamps for live applications

  Voice Management 🗣️
  List all available voices
  Get detailed information about specific voices
  Delete custom voices
  Edit voice properties (name and description)
  Find similar voices based on voice ID

  Audio Processing 🎧
  Create transcripts from audio
  Apply voice changing effects
  Generate sound effects
  Isolate audio components
  Design and preview new voices
  Save voice previews as new voices

  Requirements ⚙️
  An ElevenLabs API key
  n8n instance with HTTP Request Tool node
  MCP Server Trigger node for AI integration

  Setup 🔧
  Import the workflow into your n8n instance
  Configure your ElevenLabs API key in the workflow settings
  The workflow uses AI expressions for voice IDs with a fallback value of Z9hrfEHGU3dykHntWvIY

  Usage 📝
  All nodes are connected to the MCP Server Trigger for AI-powered interactions

  Example Use Cases 💡
  Generate natural-sounding speech from text
  Create and manage custom voices
  Process and transform audio files
  Build voice-based applications
  Integrate ElevenLabs capabilities into existing workflows

  Technical Details 🔍
  All endpoints use proper error handling
  Voice ID parameters use AI expressions with fallback values
  Nodes are organized in logical groups for better workflow management
  Includes comprehensive parameter validation
  Supports streaming and real-time processing

  Support 🤝
  For issues or questions, please refer to:
  ElevenLabs API Documentation
  n8n Documentation
  n8n Community 

nodes_used:
  ["n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","audio processing","AI/ML","voice synthesis"],"complexity":"complex","use_cases":["Text-to-speech generation (batch and streaming)","Create and manage custom voices","Real-time voice streaming with timestamps","Transcribe and process audio files","Apply voice-changing effects and sound design for media/games/apps"],"estimated_setup_minutes":20,"required_services":["ElevenLabs API (API key)","n8n instance with HTTP Request node","MCP Server (MCP Server Trigger node) for AI integration"],"key_features":["Text-to-speech with customizable voice settings","Streaming TTS (with and without timestamps)","Voice management: list, get, edit, delete, find similar","Audio processing: transcription, isolation, voicechanger, sound effects","Design/preview and save new voices (voice previews saved as new voices)"],"target_audience":["Developers building voice-enabled applications","AI/ML engineers experimenting with TTS","Audio producers and sound designers creating effects/voices"]}


name: Generate AI-Powered LinkedIn Posts with Ollama, Image Creation, and Gmail Delivery
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-06-05T05:05:57.769Z
updated_at: 2025-06-05T05:05:57.769Z
url: https://n8n.io/workflows/4674
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  This automation flow is designed to generate professional, research-backed LinkedIn posts based on a user-submitted topic and audience, enhance it with a visually aligned image prompt, and then automatically send the post and image via Gmail and/or publish it to LinkedIn.
  ⚙️ How It Works (Step-by-Step):
  📝 Form Submission (Input Trigger)

      A user fills out a form with:

          Email

          Topic of the Post

          Target Audience

      This form submission acts as the entry point of the workflow (Form Trigger node).

  🤖 LinkedIn Post Generation Agent

      An AI agent is triggered that:

          Uses Tavily API to fetch real-time web search content related to the topic.

          Processes the topic and audience data using an Ollama Chat Model.

          Generates a well-structured LinkedIn post that includes:

              Hook

              Educational insight

              Professional tone

              Source citations

              Hashtags and call to action

  🎨 Image Prompt Agent

      The generated post is passed to a second agent that:

          Extracts the core message.

          Converts it into a graphic prompt using a different Ollama LLM.

          The prompt is written to be used by an image-generation model like DALL·E or Gemma/GPT-based image tools.

  🖼️ Image Generation

      The image prompt is passed to a local image generation endpoint (localhost:8098) or OpenAI (api.openai.com) to generate a visual asset.

      The base64 image is converted into a file.

  📩 Email Dispatch

      The post text and the generated image are then sent to the user’s email address via the Gmail node.

      The email includes:

          The full LinkedIn post

          The auto-generated image as an attachment

  🔗 LinkedIn Publishing (Optional)

      If OAuth is enabled, the post can also be published directly to LinkedIn using the LinkedIn node.

  🛠️ Tools Used:

      n8n: Orchestration platform

      OpenRouter & Ollama: Local/hosted LLMs for post and prompt generation

      Tavily API: Real-time web search

      OpenAI or Local Endpoint: Image generation from text

      SMTP (Gmail): For sending emails

      LinkedIn API: For automated posting

  📦 Key Features:

      End-to-end automation from form to email/post

      Uses real-time research for accuracy

      Creative visual generation with professional branding intent

      Works locally or with cloud APIs

      Modular: Can switch tools or endpoints (OpenAI ↔ Localhost, Ollama ↔ OpenRouter)

  🚀 Ideal Use Cases:

      Marketing teams needing fast content turnaround

      Personal branding assistants

      Founders, freelancers, and executives sharing thought leadership

      University or organization-wide communication systems

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.convertToFile","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.emailSend","n8n-nodes-base.linkedIn"]

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metadata_json:
  {"categories":["automation","content creation","marketing","ai","integration"],"complexity":"complex","use_cases":["Generate research-backed LinkedIn posts from user input","Automated delivery of posts and visuals via email","Direct publishing to LinkedIn (optional)","Rapid content creation for marketing/personal branding"],"estimated_setup_minutes":90,"required_services":["n8n","Ollama (local or hosted LLM)","Tavily API (real-time web search)","OpenAI or local image-generation endpoint (e.g., localhost:8098)","Gmail SMTP / Google Workspace (OAuth)","LinkedIn API (OAuth, optional)","OpenRouter (optional)"],"key_features":["Form-driven trigger to collect topic, audience, and email","LLM agent that fetches research and generates structured LinkedIn posts with citations, hashtags, CTA","Separate LLM agent to produce image-generation prompts aligned with post messaging","Image generation via local or cloud endpoint and conversion to file attachment","Automated email dispatch with post text and image attachment via Gmail node"],"target_audience":["Marketing teams","Content creators and social media managers","Founders, freelancers, executives for personal branding posts (thought leadership) ','Developers/IT who set up integrations and automation"]}


name: Intelligent AI Digest for Security, Privacy, and Compliance Feeds
author_name: Niranjan G
author_username: niranjan
categories: []
created_at: 2025-06-05T06:11:40.248Z
updated_at: 2025-06-05T06:11:40.248Z
url: https://n8n.io/workflows/4678
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  How it works
  This workflow acts like your own personal AI assistant, automatically fetching and summarizing the most relevant Security, Privacy, and Compliance news from curated RSS feeds. It processes only the latest articles (past 24 hours), organizes them by category, summarizes key insights using AI, and delivers a clean HTML digest straight to your inbox—saving you time every day.

  Key Highlights

  Handles three independent tracks: Security, Privacy, and Compliance
  Processes content from customizable RSS sources (add/remove easily)
  Filters fresh articles, removes duplicates, and sorts by recency
  Uses AI to summarize and format insights in a digestible format
  Sends polished HTML digests via Gmail—one per category
  Fully modular and extensible—adapt it to your needs

  Personalization
  You can easily tailor the workflow:

  🎯 Customize feeds: Add or remove sources in the following Code nodes:
  Fetch Security RSS, Fetch Privacy Feeds, and Fetch Compliance Feeds

  🔧 Modify logic: Adjust filters, sorting, formatting, or even AI prompts as needed

  🧠 Bring your own LLM: Works with Gemini, but easily swappable for other LLM APIs

  Setup Instructions

  Requires Gmail and LLM (e.g., Gemini) credentials
  Prebuilt with placeholders for RSS feeds and email output
  Designed to be readable, maintainable, and fully adaptable

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.sort","n8n-nodes-base.sort","n8n-nodes-base.sort","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.splitOut","n8n-nodes-base.splitOut","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.rssFeedRead","n8n-nodes-base.splitOut","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","content curation","security monitoring"],"complexity":"complex","use_cases":["Daily security/privacy/compliance digests","Threat intelligence summarization","Executive summaries of recent incidents and regulations","Centralized monitoring of curated RSS sources","Automated email delivery of formatted insights"],"estimated_setup_minutes":20,"required_services":["n8n (workflow platform)","Gmail (email delivery)","LLM provider (e.g., Google Gemini or other LLM API)","Curated RSS feed sources"],"key_features":["Three independent tracks: Security, Privacy, Compliance","Fetches and processes RSS feeds (configurable sources)","Filters articles from the past 24 hours, removes duplicates, sorts by recency","AI-powered summarization and formatting into HTML","Sends one polished HTML digest per category via Gmail email node(s) (modular)"],"target_audience":["Security teams / SOC analysts","Privacy and compliance officers","Risk & governance teams','IT/DevOps managers looking for automated monitoring"]}


name: Daily Auto-Archive for Gmail Messages
author_name: Niranjan G
author_username: niranjan
categories: []
created_at: 2025-06-05T06:28:09.689Z
updated_at: 2025-06-05T06:28:09.689Z
url: https://n8n.io/workflows/4679
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?

  Professionals, solopreneurs, or productivity enthusiasts who want to keep their Gmail inbox clean and organized without manual effort.

  What problem does this solve?

  Manually archiving emails clutters your time and slows you down. This workflow automates inbox cleanup by removing the "INBOX" label from messages received over 24 hours ago. A perfect companion to AI-based labeling workflows, this keeps your inbox light and relevant.

  What this workflow does

  Triggers every day at 4 AM
  Fetches Gmail messages from the INBOX that are older than 24 hours
  Processes them one by one using the Split Out node
  Removes the INBOX label, effectively archiving the messages

  Setup

  Connect your Gmail account using OAuth2 credentials.
  Customize the Schedule Trigger node to adjust the run time.
  Modify the Gmail filter if you want to archive unread or labeled emails instead.

  How to customize this workflow to your needs

  Schedule different frequencies (e.g. twice a day or weekly).

  🔄 Pairs Well With

  This complements the Intelligent Email Organization with AI-Powered Content Classification workflow.

  Use that to label emails smartly using AI, and this one to auto-archive them for a clean, clutter-free inbox.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.gmail","n8n-nodes-base.splitOut","n8n-nodes-base.gmail"]

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metadata_json:
  {"categories":["automation","email management","productivity","integration"],"complexity":"simple","use_cases":["Automatically archive Gmail messages older than a set age","Keep inbox clutter-free without manual intervention","Combine with AI-based labeling workflows to auto-archive categorized emails","Scheduled inbox maintenance (daily, twice daily, weekly)"],"estimated_setup_minutes":10,"required_services":["Gmail (Google account with OAuth2 access)","n8n instance"],"key_features":["Daily scheduled trigger (configurable run time/frequency)","Fetches messages from INBOX older than 24 hours using Gmail filter","Processes messages individually with Split Out node","Removes INBOX label to archive messages","Customizable filter and schedule"],"target_audience":["Professionals","Solopreneurs","Productivity enthusiasts"]}


name: Automatic Gmail Message Categorization with GPT-4 Content Analysis & Labels
author_name: Henry
author_username: henry
categories: []
created_at: 2025-06-05T07:45:08.946Z
updated_at: 2025-06-05T07:45:08.946Z
url: https://n8n.io/workflows/4680
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?

  This workflow is ideal for Gmail users and teams who receive a high volume of emails and want to streamline inbox management. It suits professionals seeking to organize messages automatically, including sales teams, project managers, support staff, and anyone who benefits from automated email categorization.

  What problem is this workflow solving? / Use case

  Manually labeling emails is time-consuming and can lead to inconsistent organization. This automated n8n workflow uses Gmail and OpenAI to analyze incoming messages and apply the appropriate labels, such as "Quotation", "Inquiry", "Project progress", and "Notification", based on content—improving productivity and ensuring important messages are prioritized.

  What this workflow does

  The workflow retrieves new Gmail messages, analyzes their content with OpenAI, and automatically assigns pre-defined Gmail labels that match the email’s intent. This ensures emails are sorted efficiently using AI-powered content analysis and Gmail’s labeling system.

  Setup

  Ensure Gmail labels (e.g., "Quotation", "Inquiry") are created in your Gmail account.
  Connect your Gmail and OpenAI accounts as credentials in n8n.
  Import the workflow into your n8n instance and update node configurations to match your Gmail label names.

  How to customize this workflow to your needs

  Edit or add Gmail labels both in your Gmail account and within the workflow logic.
  Adjust the prompt or parameters sent to OpenAI to better match your categorization style.
  Expand or refine the list of label categories to fit your team’s or business’s requirements.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.gmailTrigger","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.splitOut","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

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metadata_json:
  {"categories":["automation","integration","email management","AI/ML","productivity"],"complexity":"medium","use_cases":["Automatically label and organize incoming Gmail messages","Prioritize important emails and route messages to teams (sales, support, PM)","Reduce manual email classification and ensure consistent organization","Analyze message intent (e.g., inquiries, quotations, notifications) for downstream automation"],"estimated_setup_minutes":15,"required_services":["Gmail (Google account)","OpenAI (GPT-4) API","n8n instance"],"key_features":["AI-powered content analysis using GPT-4","Automatic assignment of pre-defined Gmail labels","Customizable prompts and label categories","Structured output parsing for reliable label selection","Real-time processing of new incoming emails"],"target_audience":["Gmail users","Sales teams","Support teams and helpdesks\",\"Project managers\",\"Small business owners\",\"Automation/IT engineers"]}


name: Sync Google Drive files with OpenAI vector store for Assistants
author_name: Barty | @BartyDoesAI
author_username: supbarty
categories: []
created_at: 2025-06-05T08:19:42.150Z
updated_at: 2025-06-05T08:19:42.150Z
url: https://n8n.io/workflows/4681
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Keeping AI assistant knowledge up-to-date is manual and time-consuming. When documents change in Google Drive, your OpenAI vector store becomes outdated, leading to incorrect or missing information in AI responses. This workflow eliminates manual syncing by automatically detecting file changes and updating your vector store accordingly.

  How it works?

  This workflow maintains perfect sync between your Google Drive folder and OpenAI vector store. It compares existing files, detects new uploads, modifications, and deletions, then automatically updates, creates, or removes vector store entries. The workflow is designed to be efficient and reliable, handling up to 100 files per sync cycle.
  Scan Google Drive folder for all files and their modification dates
  Query OpenAI vector store to check existing files and timestamps
  Compare and identify changes - new files, updated files, or deleted files
  Sync changes automatically - upload new files, update modified files, delete removed files from vector store
  Schedule regular checks to maintain continuous sync

  Who is it for?

  Developers and teams building AI assistants that need to search through company documents, knowledge bases, or file repositories stored in Google Drive.

  Setup
  Setup takes approximately 15-20 minutes and requires configuring Google Drive and OpenAI API credentials, setting two variables (folder ID and vector store ID), and defining your sync schedule. Detailed implementation guides and credential setup tutorials are included to streamline the process.

  What's included?
  Your purchase includes comprehensive implementation support: detailed step-by-step walkthrough with screen recording, required API scopes explained clearly, tutorials for setting up Google Drive and OpenAI credentials, and access to our tech support forum for troubleshooting any implementation challenges.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.splitInBatches","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.compareDatasets","n8n-nodes-base.filter","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.switch","n8n-nodes-base.switch"]

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metadata_json:
  {"categories":["integration","automation","data processing","knowledge management"],"complexity":"medium","use_cases":["Keep AI assistant knowledge up-to-date","Automated document ingestion for RAG/semantic search","Sync company knowledge bases stored in Google Drive with a vector store","Maintain and prune vector store entries based on file changes"],"estimated_setup_minutes":20,"required_services":["Google Drive API (Google Workspace)","OpenAI API (embeddings/vector store)","n8n automation platform"],"key_features":["Scans Google Drive folder and reads modification timestamps","Queries OpenAI vector store to detect existing entries and timestamps","Detects new, modified, and deleted files via comparison logic","Creates, updates, or deletes vector store entries automatically","Batch processing (handles up to ~100 files per sync cycle) with scheduling support for continuous sync"],"target_audience":["Developers building AI assistants","ML/data engineers maintaining vector stores","Teams managing document-based knowledge bases"]}


name: Create an Image Enhancement API Endpoint with Nero AI Business API
author_name: nero
author_username: nero
categories: []
created_at: 2025-06-05T08:24:05.737Z
updated_at: 2025-06-05T08:24:05.737Z
url: https://n8n.io/workflows/4682
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works
  This template uses the n8n AI agent node as an orchestrating agent that decides which tool (knowledge graph) to use based on the user's prompt.

  How to use
  Create an account and apply for an API key on https://ai.nero.com/ai-api?utm_source=n8n-base-workflow.

  Fill your key into the Create task and Query task status nodes.
  Select an AI service and modify Create task node parameters, the API doc: https://ai.nero.com/ai-api/docs.
  Execute the workflow so that the webhook starts listening.
  Make a test request by postman or other tools, the test URL from the Webhook node.
   
  You will receive the output in the webhook response.

  Our API doc
  Please create an account to access our API docs.
  https://ai.nero.com/ai-api/docs.

  Use cases
  Large Scale Printing
  	Upscale images into ultra-sharp, billboard-ready masterpieces with 300+ DPI and billions of pixels.


  Game Assets Compression 
  	Improve your game performance with AI-Image Compression: Faster, Better & Lossless.


  E-commerce Image Editing 
  	Remove & replace your product image backgrounds, create virtual showrooms.


  Photo Retouching 
  	Remove & reduce grains & noises from images.


  Face Animation 
  	Transform static images into dynamic facial expression videos or GIFs with our cutting-edge Face Animation API


  Photo Restoration 
  	Our Al-driven Photo Restoration API offers advanced scratch removal, face enhancement, and image upscaling.


  Colorize Photo 
  	Transform black & white images into vivid colors.


  Avatar Generator 
  	Turn your selfie into custom avatars with different styles and backgrounds


  Website Compression
  	Speed up your website, compress your images in bulk.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","image-processing","ai-ml","webhooks"],"complexity":"medium","use_cases":["Image upscaling for large-scale printing","Game asset compression and optimization","E-commerce product image editing and background removal","Photo retouching and noise reduction","Face animation (static image → video/GIF generation)"],"estimated_setup_minutes":15,"required_services":["Nero AI Business API (API key/account)","n8n instance (workflow runner)","Public webhook endpoint (or tunneling tool like ngrok) for local testing","HTTP client for testing (Postman or curl)"],"key_features":["n8n AI agent orchestration to choose appropriate Nero API tool based on prompt","Create task and Query task status flow for asynchronous image processing","Webhook trigger and immediate response with processed output","Supports upscaling, compression, background removal, restoration, colorization, face animation, avatar generation","Configurable AI service parameters via nodes"],"target_audience":["Developers integrating image-enhancement APIs","E-commerce teams managing product imagery","Game developers optimizing assets and textures"]}


name: Slack-OpenAI Assistant Integration for Direct Messages & @mentions
author_name: Barty | @BartyDoesAI
author_username: supbarty
categories: []
created_at: 2025-06-05T08:34:30.153Z
updated_at: 2025-06-05T08:34:30.153Z
url: https://n8n.io/workflows/4683
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Getting AI assistance in Slack requires switching between apps and losing conversation context. Teams waste time copying messages to ChatGPT, losing the flow of their work discussions. This workflow brings OpenAI Assistant directly into your Slack workspace, responding to direct messages and @mentions while maintaining conversation memory and context.

  How it works?

  This workflow creates an intelligent Slack bot powered by OpenAI Assistant that responds naturally to team communications. It handles both direct messages and @mentions, maintains conversation history, and provides contextual responses without leaving your Slack workspace.
  Listen for Slack events - detects direct messages and @mentions while filtering out bot responses to prevent loops
  Process message types - handles both assistant mode (DMs) and public channel @mentions
  Set typing indicator - shows customizable "thinking" status for natural conversation flow
  Generate AI response - uses your configured OpenAI Assistant with custom instructions and knowledge base
  Maintain conversation memory - tracks context across up to 5 recent messages per session
  Reply intelligently - responds in threads for @mentions, direct messages for DMs

  Who is it for?

  Teams and organizations wanting to integrate AI assistance directly into their Slack workflows. Perfect for customer support teams, internal help desks, or any group that needs quick access to AI-powered responses without leaving their communication platform.

  Setup

  Setup takes approximately 20-25 minutes and requires configuring Slack app permissions with proper bot user filtering, OpenAI Assistant credentials, and customizing response behavior. The workflow includes built-in loop prevention and conversation threading for organized discussions.

  What's included?

  Your purchase includes comprehensive implementation support: detailed step-by-step walkthrough with screen recording, complete Slack app configuration guide with required scopes and permissions, OpenAI Assistant setup tutorial, conversation memory configuration, and access to our tech support forum for troubleshooting any implementation challenges.

nodes_used:
  ["n8n-nodes-base.switch","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.slackTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.slack","n8n-nodes-base.httpRequest"]

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metadata_json:
  {"categories":["automation","integration","communication","ai-assistant"],"complexity":"medium","use_cases":["Provide AI assistance in Slack via direct messages and @mentions","Internal help desk and employee support","Customer support triage and first-response","Quick access to knowledge base answers without leaving Slack","Maintain conversational context across messages"],"estimated_setup_minutes":25,"required_services":["Slack (workspace & app with proper bot scopes)","OpenAI Assistant / OpenAI API credentials","n8n instance to host the workflow","Optional: external knowledge base or vector DB for enhanced context (e.g., Pinecone, Supabase)"],"key_features":["Listens for Slack events (DMs and @mentions) and filters bot messages","Sets typing indicator for natural conversation flow","Generates responses via configured OpenAI Assistant with custom instructions","Maintains conversation memory (tracks up to 5 recent messages per session)","Replies in threads for channel mentions and DMs for direct messages to keep context organized and prevent loops"],"target_audience":["Customer support teams","Internal help desks / IT support","Operations and product teams wanting quick knowledge access in Slack"]}


name: AI-Powered Meta Ads Analysis & Creation with Gemini, GPT-4.1 Mini & Ads Manager
author_name: Daniel Setzermann
author_username: danielsetzermann
categories: []
created_at: 2025-06-05T09:09:39.117Z
updated_at: 2025-06-05T09:09:39.117Z
url: https://n8n.io/workflows/4684
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  AI-Powered Meta Ads Creation & Analysis Workflow

  Overview

  This comprehensive n8n workflow automates the entire Meta (Facebook/Instagram) advertising process, from asset analysis to ad creation. It combines AI-powered content analysis with automated ad deployment, streamlining the creation of high-converting social media advertisements.



  Watch a quick video walkthrough of the workflow

  Key Features

  🤖 AI-Powered Asset Analysis
  Video Analysis**: Uses Google Gemini to analyze video content, extracting transcripts, scene descriptions, hooks, offers, and branding elements
  Image Analysis**: Employs GPT-4.1 Mini to analyze static images, identifying visual elements, USPs, and marketing potential
  Structured Output**: Generates detailed descriptions and creative insights for informed ad creation

  ✍️ Automated Ad Copy Generation
  Creates 3 variations each of primary text, headlines, and link descriptions
  Optimized for Meta's character limits and best practices
  Maintains brand voice and messaging consistency
  Leverages AI analysis to create compelling, conversion-focused copy

  🎯 Meta Ads Manager Integration
  Video Ads**: Uploads videos, creates ad creatives with multiple text variations
  Image Ads**: Supports both single and multi-image campaigns (1:1 and 9:16 formats)
  Asset Feed Optimization**: Implements placement-specific customization rules
  Automated Preview Generation**: Creates ad previews for different placements

  📊 Smart Workflow Management
  Google Drive Integration**: Monitors designated folders for new creative assets
  Google Sheets Tracking**: Maintains comprehensive records of all assets and campaigns
  Status Management**: Tracks processing stages and prevents duplicate work
  Error Handling**: Includes retry logic and status checking for reliable operation

  Workflow Components

  Asset Discovery & Processing
  Google Drive Trigger: Monitors specified folder for new image/video files
  File Analysis: Extracts metadata, dimensions, and file specifications
  Asset Registration: Logs all assets in Google Sheets for tracking

  AI Analysis Pipeline
  Content Type Detection: Automatically identifies videos vs. images
  Video Processing:
     Uploads to Google Gemini for analysis
     Generates comprehensive content breakdown
     Extracts all marketing-relevant elements
  Image Processing:
     Analyzes visual content with GPT-4.1 Mini
     Identifies key messaging and visual elements
     Creates detailed creative descriptions

  Ad Copy Creation
  AI Agent Processing: Transforms analysis into marketing copy
  Multi-Variant Generation: Creates 3 versions of each text element
  Platform Optimization: Ensures compliance with Meta's requirements
  Quality Assurance: Structured output validation

  Meta Ads Deployment
  Asset Upload: Pushes images/videos to Meta Ads Manager
  Creative Assembly: Builds ad creatives with generated copy variations
  Campaign Creation: Sets up ads with proper targeting and placement rules
  Status Tracking: Updates spreadsheet with campaign IDs and status

  Setup Requirements

  Required Credentials
  Meta Developer Account**: App access token for Meta Graph API
  Google Drive OAuth**: For file monitoring and asset access
  Google Sheets OAuth**: For workflow tracking and management
  Google Gemini API**: For video analysis capabilities
  OpenAI API**: For image analysis and copy generation

  Configuration Steps
  Google Drive Setup: 
     Create dedicated folder for creative assets
     Configure folder monitoring in the trigger node
  Google Sheets Template:
     Use provided template for asset and campaign tracking
     Configure account settings and campaign parameters
  Meta Developer Setup:
     Create Meta App and obtain access tokens
     Set up ad account permissions
  API Credentials:
     Configure all required authentication credentials
     Test connections before activation

nodes_used:
  ["n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.filter","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.switch","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.filter","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4648 characters]

metadata_json:
  {"categories":["automation","advertising","AI/ML","integration","asset management"],"complexity":"complex","use_cases":["Automated Meta (Facebook/Instagram) ad creation and deployment","Video and image content analysis for creative insights","Multi-variant ad copy generation optimized for Meta placements","Asset monitoring and tracking via Google Drive/Sheets","Automated campaign/creative assembly and status tracking"],"estimated_setup_minutes":120,"required_services":["Meta Graph API / Ads Manager (Meta Developer account & app token)","Google Drive (OAuth)","Google Sheets (OAuth)","Google Gemini API (video analysis)","OpenAI API (GPT-4.1 Mini for image analysis & copy)","n8n runtime/host"],"key_features":["AI-powered video analysis (transcripts, scenes, hooks, offers)","AI image analysis and structured creative descriptions","Generates 3 variations of primary text, headlines, link descriptions","Uploads assets and builds creatives in Meta Ads Manager (video & image ads)","Placement-specific asset/feed optimization and ad previews generation for multiple formats (1:1, 9:16)"],"target_audience":["performance marketers","ad operations teams","digital marketing agencies/growth teams`,`developers/automation engineers"]}


name: Lead Generation Automate on LinkedIn - Personalisation, Enrichment
author_name: Krupal Patel
author_username: krupalpatel
categories: []
created_at: 2025-06-05T10:57:25.716Z
updated_at: 2025-06-05T10:57:25.716Z
url: https://n8n.io/workflows/4685
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  🔧 Workflow Summary

  This system automates LinkedIn lead generation and enrichment in six clear stages:

  1. Lead Collection (via Apollo.io)
  Automatically pulls leads based on keywords, roles, or industries using Apollo’s API.
  Captures name, job title, company, and LinkedIn profile URL.
  You can kick off the workflow via form, webhook, WhatsApp, Telegram, or any other custom trigger that passes search parameters.

  2. LinkedIn Username Extraction
  Extracts usernames from LinkedIn profile URLs using a script step.
  These usernames are required for further enrichment using RapidAPI.

  3. Email Retrieval (via Apollo.io User ID)
  Fetches verified work email using the Apollo User ID.
  Email validity is double-checked using www.mails.so filtering out undeliverable or inactive emails by checking MX records and deliverability.

  4. Profile Summary (via LinkedIn API on RapidAPI)
  Enriches lead data by pulling bio/summary details to understand their background and expertise.

  5. Activity Insights (Posts & Reposts)
  Collects recent posts or reposts to help craft personalised messages based on what they’re currently engaging with.

  6. Leads Sheet Update
  All data is written into a Google Sheet.
  New columns are populated dynamically without erasing existing data.

  ⸻

  ✅ Smart Retry Logic

  Each workflow is equipped with a fail-safe system:
  Tracks status per row: ✅ done, ❌ failed, ⏳ pending
  Failed rows are automatically retried after a custom delay (e.g., 2 weeks).
  Ensures minimal drop-offs and complete data coverage.

  📊 Google Sheets Setup

  Make a copy of the following:
  Template 1: Apollo Leads Scraper & Enrichment
  Template 2: Final Enriched Leads 

  The system appends data (like emails, bios, activity) step by step.

  🔐 API Credentials Needed

  1. Apollo API
  Sign up and generate API key at Apollo Developer Portal
  Be sure to enable the “Master API Key” toggle so the same key works for all endpoints.

  2. LinkedIn Data API (via RapidAPI)
  Subscribe at RapidAPI - LinkedIn Data
  Use your key in the x-rapidapi-key
   header.

  3. Mails.so API
  Get your API Key from mails.so dashboard

  🛠️ Troubleshooting – LinkedIn Lead Machine

  ✅ Common Mistakes & Fixes

  1. API Keys Not Working
  Make sure API keys for Apollo, RapidAPI, and mails.so are correct.
  Apollo “Master API Key” must be enabled.
  Keys should be saved as Generic Credentials in n8n.

  2. Leads Not Found
  Check if the search query (keyword/job title) is too narrow.
  Apollo might return empty results if the filters are incorrect.

  3. LinkedIn URLs Missing or Invalid
  Ensure Apollo is returning valid LinkedIn URLs.
  Improper URLs will cause username extraction and enrichment steps to fail.

  4. Emails Not Coming Through
  Apollo may not have verified emails for all leads.
  mails.so might reject invalid or expired email addresses.

  5. Google Sheet Not Updating
  Make sure the Google Sheet is shared with the right Google account (linked to n8n).
  Check if the column names match and data isn’t blocked due to formatting.

  6. Status Columns Not Changing
  Each row must have done, failed, or pending in the status column.
  If the status doesn’t update, the retry logic won’t trigger.

  7. RapidAPI Not Returning Data
  Double-check if username is present and valid.
  Make sure the RapidAPI plan is active and within limits.

  8. Workflow Not Running
  Check if the trigger node (form, webhook, etc.) is connected and active.
  Make sure you’re passing the required inputs (keyword, role, etc.).

  Need Help? Contact www.KrupalPatel.com for support and custom workflow development

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.limit","n8n-nodes-base.limit","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 11392 characters]

metadata_json:
  {"categories":["automation","integration","lead generation","data enrichment","sales enablement"],"complexity":"complex","use_cases":["Automated LinkedIn lead scraping","Lead enrichment with bios and activity","Verified email retrieval and validation","Personalised outreach data preparation","Maintaining and updating lead lists in Google Sheets"],"estimated_setup_minutes":60,"required_services":["Apollo API","LinkedIn Data API (via RapidAPI)","mails.so API","Google Sheets (Google account)","OpenAI API (optional for personalization)","n8n (workflow runtime)"],"key_features":["Automated lead collection from Apollo by keyword/role/industry","LinkedIn username extraction from profile URLs","Email lookup via Apollo user ID and MX/deliverability checks via mails.so","Profile summary and recent activity enrichment (posts/reposts) via RapidAPI","Writes/enriches rows in Google Sheets without overwriting existing data and appends new columns dynamically"],"target_audience":["Sales development reps (SDRs)","Growth teams and marketers","Recruiters sourcing candidates on LinkedIn"]}


name: Automate Customer Feedback Analysis with Forms, AI, Google Sheets and WhatsApp
author_name: OneClick IT Consultancy P Limited
author_username: oneclick-it
categories: []
created_at: 2025-06-05T11:01:31.970Z
updated_at: 2025-06-05T11:01:31.970Z
url: https://n8n.io/workflows/4686
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Automate Customer Feedback Analysis with Google Sheets, WhatsApp, and Email

  Introduction: Drowning in Data, Starving for Insight?
  Imagine this: Your team launches a new feature. Feedback starts pouring in emails, support tickets, social media mentions, and survey responses. You know gold is buried in there, but manually reading, tagging, and summarising hundreds, maybe thousands, of comments? It takes days, maybe weeks. By the time you have a clear picture, the moment might have passed. Sounds exhausting, right?

  What if you could have an AI assistant tirelessly working 24/7, instantly analysing every piece of feedback the moment it arrives? This isn't science fiction anymore. AI-powered automation can transform this slow, manual chore into a real-time insight engine, giving you the pulse of your customer base almost instantly. Let's explore how.

  What's the Goal? Understanding the Workflow Objective
  The core challenge is transforming raw, unstructured customer feedback into actionable intelligence quickly and efficiently.

  The Problem:
  Manual Overload: Sifting through vast amounts of feedback manually is incredibly time-consuming and prone to human error or bias.
  Delayed Insights: The lag between receiving feedback and understanding it means missed opportunities and slow responses to critical issues.
  Inconsistent Analysis: Different team members might interpret or categorize feedback differently, leading to unreliable trend spotting.

  The AI Solution:
  Automated Data Collection: Connects directly to feedback sources (surveys, social media, review sites, helpdesks).
  AI-Powered Analysis: Uses Large Language Models (LLMs) like GPT-4 or Claude to analyze sentiment, extract key topics, and summarize comments.
  Intelligent Categorization: Automatically tags feedback based on predefined or dynamically identified themes (e.g., "bug report," "feature request," "pricing issue").
  Real-time Reporting: Pushes structured insights into dashboards, databases, or triggers notifications for immediate awareness.

  Outcome: You move from reactive problem-solving based on stale data to proactive, strategic decisions driven by a near real-time understanding of customer sentiment and needs.

  Why Does It Matter? Achieving 100X Productivity and Efficiency
  Look, automating feedback isn't just about saving time; it's about scaling your ability to listen and respond smarter, not harder. When you leverage AI, the gains aren't incremental - they're exponential.

  Here’s why this is a game changer:

   Blazing Speed: Analyse feedback 100x Faster (or more!) than manual methods. Insights appear in minutes or hours, not days or weeks.
   Unhuman Scalability: Process virtually unlimited volumes of feedback without needing to scale your human team proportionally. AI doesn't get tired or bored.
   Consistent Accuracy: AI applies analysis rules consistently, reducing human bias and ensuring reliable categorisation and sentiment scoring over time.
   Proactive Trend Spotting: Identify emerging issues or popular requests much earlier by analysing aggregated data automatically. Spot patterns humans might miss.
   Free Up Your Team: Let your talented team focus on acting on insights – improving products, fixing issues, engaging customers – instead of drowning in data entry.

  How It Works: AI Automation Step by Step
  Getting this set up is more straightforward than you might think, especially with tools like n8n acting as the central hub.

  Automated Feedback Triggering
  CRM/Website Event Node
   Trigger feedback requests after:
   Purchases (eCommerce)
   Support ticket resolution
   Feature usage (SaaS)
   
  Time-Based Node
   Schedule recurring NPS surveys
   Customer health check-ups

  Chat App Node (WhatsApp/Telegram/Messenger)
   Send conversational feedback prompts:
   "How was your recent experience with [specific interaction]?"

  Multi-Channel Feedback Collection
  Email Node (SendGrid/Mailchimp)
   Send personalized feedback requests
   Embed 1-5 rating widgets

  SMS Node (Twilio)
   Short mobile surveys:
   "Reply 1-5: How satisfied with your purchase?"

  Webhook Node
   Capture in-app feedback
   Process chatbot responses

  Social Media Node
   Monitor Twitter/X, Instagram mentions
   Analyze comments for unsolicited feedback

  AI-Powered Real-Time Analysis
  OpenAI/ChatGPT Node (Sentiment Analysis)
   Prompt: "Analyze sentiment (positive/neutral/negative) and key themes from: [customer feedback]"
   Output fields:
   Sentiment score (1-5)
   Urgency flag (high/medium/low)
   Key topics (billing, support, product, etc.)
   
  Translation Node (Optional)
   Convert multilingual feedback into a consistent language

  Instant AI Response System
  Conditional Node (Routing Logic)
   Positive feedback → Send thank-you + referral ask
   Neutral feedback → Follow-up question for details
   Negative feedback → Escalate to the human team

  AI Response Generator Node
   Prompt: "Create a personalized response to [feedback type] about [topic] with sentiment [score]"
   Adjust tone (professional/friendly/empathetic)

  Escalation Node
   Route critical issues to the support team with full context

  Automated Insights & Alerts
  Dashboard Node
   Real-time sentiment tracking
   Emerging issue detection

  Alert Node (Slack/Teams/Email)
   Notify teams of negative trends:
   "3+ complaints about checkout flow in the past hour!"

  Report Node
   Auto-generate weekly/monthly summaries:
   "Top 5 customer pain points this week"

  Product Board Integration
   Auto-create feature requests
   Prioritize based on feedback volume

  Tools of the Trade: AI & Automation Tech Stack
  You don't need a massive, complex tech stack. Focus on a few core, powerful tools:
   n8n: The workflow automation platform. This is the 'glue' that connects everything and orchestrates the process without needing deep coding knowledge. Honestly, it's incredibly versatile.
   OpenAI (GPT-4/GPT-4o): State-of-the-art LLM for high-quality text analysis, summarization, and classification. Great for complex understanding.
   Anthropic (Claude 3 Sonnet/Opus): Another top-tier LLM, known for strong performance in analysis and handling large contexts. Often, a great alternative or complement to GPT models.
   Feedback Sources APIs: Connectors for where your feedback lives (e.g., Typeform, SurveyMonkey, Twitter API, Zendesk API, Google Play/App Store review APIs).
   Data Storage/Destination: Where the processed insights go (e.g., Google Sheets, Airtable, Notion, PostgreSQL database, BigQuery).
   (Optional) Visualization Tool: Tools like Metabase, Grafana, Looker Studio, or Power BI to create dashboards from your structured feedback data.

  What's the Cost? Estimated Budget
  Let's talk investment. You're mainly looking at:
   Setup Costs: Primarily your time (or a consultant's) to design and build the initial workflow in n8n. Depending on complexity, this could range from a few hours to a few days. No major software licenses are usually needed upfront if using self-hosted n8n or starting with free/low-tier cloud plans.
   AI API Calls: You pay per usage to OpenAI/Anthropic. Costs depend heavily on volume but can start from $20-$50/month for moderate usage and scale up. Newer models are getting more cost-effective.
   n8n Hosting: Free if self-hosted (requires a server), or tiered cloud pricing starting around $20/month.
   Feedback Source APIs: Some platforms might have API access costs or rate limits on free tiers.
   Total Estimated Monthly Cost: For many businesses, ongoing costs can range from $50 - $500+ per month, highly dependent on feedback volume and AI model choice.

  The Return on Investment (ROI) is typically rapid. Consider the hours saved from manual analysis, the value of faster issue resolution, preventing churn, and the benefits of making product decisions based on real-time data. It often pays for itself very quickly.

  Who Benefits? Target Users and Industries
  This automated feedback loop isn't niche; it's valuable across many sectors and roles:

  Top Industries:
   SaaS (Software as a Service): Understanding user friction, feature requests, bug reports.
   E-commerce & Retail: Analyzing product reviews, post-purchase surveys, and support chats.
   Hospitality & Travel: Processing guest reviews, survey feedback.
   Mobile Apps: Monitoring app store reviews, in-app feedback.
   Financial Services: Gauging customer satisfaction with services, identifying pain points.
   
  Key Roles:
   Product Managers: Prioritizing features, understanding user needs, tracking launch reception.
   Customer Experience (CX) / Success Managers: Monitoring customer health, identifying churn risks, and improving support processes.
   Marketing Teams: Understanding brand perception, campaign feedback, and voice of the customer.
   Support Leads: Identifying recurring issues, measuring support quality, spotting training needs.
  This approach works for businesses of all sizes, from startups wanting to stay lean and agile to large enterprises needing to manage massive feedback volumes.

  How to use workflow?
  Importing a workflow in n8n is a straightforward process that allows you to use pre-built or shared workflows to save time. Below is a step-by-step guide to import a workflow in n8n, based on the official documentation and community resources.

  Steps to Import a Workflow in n8n
  1. Obtain the Workflow JSON
  Source the Workflow:**
  	Workflows are typically shared as JSON files or code snippets. You might receive them from:
  	The n8n community (e.g., n8n.io workflows page).
  	A colleague or tutorial (e.g., a .json file or copied JSON code).
  	Exported from another n8n instance (see export instructions below if needed).
  Format:** Ensure you have the workflow in JSON format, either as a file (e.g., workflow.json) or as text copied to your clipboard.

  2. Access the n8n Workflow Editor
  Log in to n8n:**
  	Open your n8n instance (via n8n Cloud or your - self-hosted instance).
  	Navigate to the Workflows tab in the n8n dashboard.
  Open a New Workflow:**
  	Click Add Workflow to create a blank workflow, or open an existing workflow if you want to merge the imported workflow.

  3. Import the Workflow
  Option 1: Import via JSON Code (Clipboard):
  In the n8n editor, click the three dots (⋯) in the top-right corner to open the menu.
  Select Import from Clipboard.
  Paste the JSON code of the workflow into the provided text box.
  Click Import to load the workflow into the editor.

  Option 2: Import via JSON File:
  In the n8n editor, click the three dots (⋯) in the top-right corner.
  Select Import from File.
  Choose the .json file from your computer.
  Click Open to import the workflow.

  Note: If the workflow includes nodes for apps requiring credentials (e.g., Google Sheets), you’ll need to configure those credentials separately after importing.

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.whatsApp","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4244 characters]

metadata_json:
  {"categories":["automation","integration","data processing","customer feedback","AI/ML"],"complexity":"medium","use_cases":["Automated sentiment analysis of customer feedback","Real‑time routing/escalation of negative feedback","Topic extraction and tagging (feature requests, bugs, pricing)","Auto-generation of personalized responses","Aggregating multi‑channel feedback into Google Sheets or dashboards for reporting and trend detection"],"estimated_setup_minutes":120,"required_services":["n8n","OpenAI (GPT-4) or Anthropic (Claude)","Google Sheets","WhatsApp API (e.g., Twilio WhatsApp)","Email provider (SendGrid/Mailchimp)","Feedback source APIs (Typeform, Zendesk, Twitter/X, App Store/Play Store)","Optional: dashboard tools (Looker Studio, Metabase)"],"key_features":["Multi‑channel feedback collection (webhooks, email, SMS, chat, social)","AI‑powered sentiment scoring and theme extraction","Automatic translation for multilingual feedback","Conditional routing (thank you, follow‑up, escalate)","AI response generation customized by sentiment and topic"],"target_audience":["Product Managers","Customer Experience / Success Managers","Support Leads and Operations Teams」「Marketing Teams」「Developers / Automation Engineers"]}


name: AI Email Organizer for GMail - Advanced Email Management & Sorting
author_name: Milan Vasarhelyi - SmoothWork
author_username: vasarmilan
categories: []
created_at: 2025-06-05T11:49:49.978Z
updated_at: 2025-06-05T11:49:49.978Z
url: https://n8n.io/workflows/4687
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Video Introduction

  Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin

  Transform your messy inbox into a calm, organized command center - in minutes - using this ready-to-use n8n automation! 

  Tired of your Gmail looking like this?  


  With this template, you can have this instead:  

  What does this automation do?

  AI-powered categorization:** Every new email is analyzed with OpenRouter AI and sorted into categories you define (like Orders, Support, Invoices, Urgent, etc.).
  Instant color-coded labels:** The workflow creates and applies Gmail labels with custom colors, so you can spot important messages at a glance.
  Supports Gmail’s Multiple Inboxes:** Display different categories in their own sections—see what matters most right away.
  Flexible and customizable:** You control the categories and definitions using a simple Google Sheet.

  How it works – Step by Step

  See the full setup & demo:  


  Copy the Template  
     Open the n8n workflow template and click Use for free.
     Log in (or sign up) for n8n Cloud for the quickest start.

     

  Customize Your Categories in Google Sheets  
     Use the provided Google Sheets template linked in the workflow notes.
     Go to File → Make a copy to your own Drive.
     Edit the categories and their definitions for your business.
     
     Example:  
     
     
     Add categories like “Existing Order Questions,” define each one to guide the AI, and copy your Google Sheet’s URL into the workflow config node.

     

  Connect AI with OpenRouter  
     Go to OpenRouter.ai, log in, and generate a new API key.
     Paste your API key into the workflow where prompted.

     

  Test and Activate the Workflow  
     Connect your Gmail account to n8n.
     Hit “Test Workflow”—watch as the AI processes your latest emails and applies labels automatically.

     

     Labels will appear instantly in Gmail, and any missing ones are created by the automation.
     
     

  Schedule Automatic Runs  
     Switch workflow status to Active in n8n.
     Set the scheduler trigger—most people use hourly, but you can use crontab.guru for custom times (like only business hours).

  Tips for Best Results

  Color Code Your Labels:**  
    In Gmail, you can assign colors to labels—set high-priority categories (like “Customer Complaints”) to a bright color to stand out.
    
    

  Upgrade Your Gmail View:**  
    Enable Multiple Inboxes in Gmail’s settings and set up sections for your key categories. Example search queries:
    in:inbox label:customer-complaints OR label:urgent-emails
    in:inbox label:existing-order-questions
    in:inbox label:support-requests

  Why Use This?

  Get rid of inbox chaos for good - no more lost emails or missed deadlines
  Fully customize the system to your business with just a Google Sheet
  Works with zero coding - set up in 10-15 minutes
  Flexible: add auto-replies, draft suggestions, and more as you grow

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.splitInBatches","n8n-nodes-base.filter","n8n-nodes-base.gmail","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4720 characters]

metadata_json:
  {"categories":["automation","integration","email management","AI","productivity"],"complexity":"medium","use_cases":["Automated email triage and categorization","Apply color-coded Gmail labels and organize inbox","Surface urgent or high-priority messages","Route/support ticket sorting and prioritization","Invoice/order detection and tracking"],"estimated_setup_minutes":15,"required_services":["Gmail (Google account)","Google Sheets (Drive)","OpenRouter.ai (AI API key)","n8n Cloud or self-hosted n8n"],"key_features":["AI-powered email categorization using OpenRouter","Creates and applies Gmail labels automatically","Color-coded labels for quick visual scanning","Categories configurable via a Google Sheet","Supports Gmail Multiple Inboxes view integration with label queries','Scheduler for periodic processing and automation"],"target_audience":["small businesses","customer support teams","founders/solopreneurs」「operations/office managers"]}


name: Zendesk: Visual Summarization, Sentiment Analysis, and Slack Integration
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-06-05T13:01:17.102Z
updated_at: 2025-06-05T13:01:17.102Z
url: https://n8n.io/workflows/4688
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Analyze and Explore your ZenDesk Support Requests using AI-Powered Knowledge Graph

  This template helps you create an interactive InfraNodus knowledge graph for your ZenDesk tickets using any search criteria (e.g. after a certain date, specific status, sender, keyword) that will automatically be sent to a selected Slack channel.

  Here's an example of the InfraNodus graph that shows the main topics and gaps in ZenDesk support tickets: 

  You can use the workflow to:

  Get an instant overview of the main topics your customers are talking about
  Generate business and product ideas based on the blind spots identified using the InfraNodus AI
  See which topics correlate to the negative / positive sentiment understanding the weak and strong sides of your product and support 
  Receive daily notifications on the main topics your customers are talking about via Slack / Telegram / Email and other channels
  Perform detailed search using a password-protected web form for tickets filtered by a certain date, status, tag, sender, keyword.
  Use the interactive graph to explore specific topics and concepts your customers are talking about — a great way to engage with their concerns in a non-linear way, bypassing the boring tabular interface
  Use the graph to explore the support requests by specific segments — e.g. status, priority, sentiment, tags, urgency.
  Use the graph generated as an AI expert available to your AI agents in other n8n workflows via InfraNodus GraphRAG. For instance, you could connect your knowledge base to the support tickets graph and let the agent discover possible solutions to your customers' most typical problems. See an sample template here.

  How it works
  You can start this workflow 

  manually, 
  with a daily / weekly trigger, or 
  via a password-protected web form, where you can provide search requests. 

  Once started, it will perform a ZenDesk tickets search with the default or your custom criteria. Then it will use the search results to generate an InfraNodus graph (or add the new data to an existing one), and — finally — use the InfraNodus AI endpoints to generate a topical summary and a product business idea based on the blind spots identified. The results are delivered a channel of your choice.

  Here's a description step by step:

  Start the workflow (manually or on schedule)
  Assign values to variables (search criteria, graph name)
  Perform ZenDesk support tickets search
  Convert the data received and submit it to InfraNodus to generate a knowledge graph
  Generate topical summary with InfraNodus
  Generate a business idea with InfraNodus (you can also change the setting to generate a question instead)
  Send a notification via Slack / Telegram / Email or back to the webform

  How to use

  You need an InfraNodus API account and key to use this workflow. You also need a ZenDesk account. It takes about 5 minutes to set everything up.

  Create an InfraNodus account.
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  Add the authorization key to all the InfraNodus HTTP nodes in the template (Steps 3, 5, and 6).
  Generate a ZenDesk authorization token following the instructions in n8n's ZenDesk node (Step 3).
  Optionally: connect your Slack or Telegram or Gmail account to receive automated notifications with the link to the graph, once the workflow is ready (it takes about 30 seconds to run).
  Run it with using the form to play around with the search criteria that works best for you (you can leave everything empty at first), then choose the parameters you like and activate the Daily Trigger node to receive executive summaries to a channel of your choice.
  Open the graph in InfraNodus and use our customer feedback analysis guide to explore the graph and generate new insights.

  Requirements

  An InfraNodus account and API key
  A ZenDesk API key
  (Optional) — a Slack / Telegram / Gmail connection for notifications

  FAQ

  1. What are the best use cases to try?

  I love to set the graph to deliver me a daily visual briefing of what's happening in my support portal. It shows me the main topics and gaps and generates product ideas based on them. Great to keep the pulse on the business. 

  I also really like generating a graph for the past week manually, using the form, and then exploring the graph in InfraNodus directly using the customer feedback analysis workflow to:

  discover main topics my customers are talking about?
  understand the topics that have the most negative connotation for them (using the sentiment filter)?
  discover some support tickets that need more attention or that talk about the topics I'm personally interested in and engage with the client
  identify the gaps in your customers' discourse based on the blind spots — useful for generating ideas, see the graph below with a demo of how it works:




  2. Why use the graph and not just AI summary?

  AI summary will just give you generic results. You'll see what you already know. Using the graph helps you deconstruct the discourse and get a much more nuanced understanding of the main pain points and interests of your customers. The auto-generated InfraNodus summary and business ideas have a direct explainable connection to the discourse, so you can always see where they are coming from and maintain the focus on all the topics, rather than the most prominent ones. 

  Additionally, having an interactive graph opens a possibility to explore your customers' concerns in a more engaging way, finding the topics and concepts that are relevant to your interests or to your agents' expertise, helping you find the conversations that you'd otherwise have missed.


  3. Is my customers' data safe?

  Absolutely. InfraNodus' terms of use and privacy policy state that the customers' data and text graphs are not used in AI training and are not offered to any third parties. Its underlying API system uses the Open API which explicitly states that data is not used for training either. So all the customers' data are private and safe. As an extra precaution, you can always delete the graphs after you analyzed them, in which case there is no trace of this data left on the servers.

  Customizing this workflow

  Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20447530961308-Zendesk-Tickets-Summarization-Sentiment-Analysis-and-Slack-Integration-with-n8n-and-InfraNodus

  For support with this template, please, contact 
  https://support.noduslabs.com

  For more InfraNodus n8n workflows, please, see our creators page:
  https://n8n.io/creators/infranodus/

  To learn more about InfraNodus, GraphRAG, and knowledge graph analysis:
  https://infranodus.com

nodes_used:
  ["n8n-nodes-base.zendesk","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.gmail","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.slack","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.form","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8392 characters]

metadata_json:
  {"categories":["integration","data processing","customer support","analytics","notifications"],"complexity":"medium","use_cases":["Visual summarization of Zendesk tickets using knowledge graphs","Sentiment analysis and highlighting topics with negative/positive connotations","Daily or on-demand executive briefings to Slack/Telegram/Email","Interactive exploration of customer feedback via InfraNodus graphs","Generating product/business ideas from discourse blind spots (GraphRAG)"],"estimated_setup_minutes":5,"required_services":["InfraNodus API (API key)","Zendesk API (token)","n8n (automation platform)","Optional: Slack (for notifications)","Optional: Telegram (for notifications)","Optional: Gmail (for email notifications)"],"key_features":["Create/append an InfraNodus knowledge graph from Zendesk search results","Auto-generate topical summaries and business ideas using InfraNodus AI","Sentiment filtering and topic correlation (negative/positive)","Multiple triggers: manual, scheduled, or password-protected web form","Deliver results to Slack/Telegram/Email and expose graph link for exploration or GraphRAG use"],"target_audience":["Support teams","Product managers","Customer success managers/operations teams (CX) (note: trimmed)"]}


name: Build a Chatbot with Reinforced Learning Human Feedback (RLHF) and RAG
author_name: NovaNode
author_username: thomasgpt
categories: []
created_at: 2025-06-05T13:39:18.776Z
updated_at: 2025-06-05T13:39:18.776Z
url: https://n8n.io/workflows/4689
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?
  This template is designed for internal support teams, product specialists, and knowledge managers who want to build an AI-powered knowledge assistant with retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF) via Telegram.

  What problem is this workflow solving?
  Manual knowledge management and answering support queries can be time-consuming and error-prone. This solution automates importing and indexing official documentation into MongoDB vector search and enhances AI responses with Telegram-based user feedback to continuously improve answer quality.

  What these workflows do
  Workflow 1: Document ingestion & indexing
  Manually triggered workflow imports product documentation from Google Docs.
  Documents are split into manageable chunks and embedded using OpenAI embeddings.
  Embedded document chunks are stored in MongoDB Atlas vector store to enable semantic search.

  Workflow 2: Telegram chat with RLHF feedback loop
  Listens for user messages via Telegram bot integration.
  Uses vector similarity search on MongoDB to retrieve relevant documentation chunks.
  Generates answers with OpenAI GPT-4o-mini model using retrieval-augmented generation.
  Sends answers back via Telegram and waits for user feedback (approval or disapproval).
  Captures feedback, maps it as positive or negative, and stores it with the conversation data for future model improvement.

  Setup
  Setting up vector embeddings
  Authenticate Google Docs and connect your Google Docs URL containing the product documentation you want to index.
  Authenticate MongoDB Atlas and connect the collection where you want to store the vector embeddings. Create a search index on this collection to support vector similarity queries. 
  Ensure the index name matches the one configured in n8n (data_index). 
  See the example MongoDB search index template below for reference.

  Setting up chat with Telegram RLHF
  Create a bot in Telegram with @botFather using the /newbot command.
  Connect the MongoDB database and search index used for vector search in the previous workflow. Also create two new collections in MongoDB Atlas: one for feedback and one for chat history. Create a search index for feedback, copying the provided template.
  Configure the AI system prompt in the “Knowledge Base Agent” node, making sure it references all three tools connected (productDocs, feedbackPositive, feedbackNegative) as provided in the template prompt.
  Make sure
  Product documentation and feedback collections must connect to the same MongoDB database.
  There are three distinct MongoDB collections: one for product documentation, one for feedback, and one for chat history (chat history collection can be separate).
  Telegram API credentials are valid and webhook URLs are correctly set up.

  MongoDB Search Index Templates
  Documentation Collection Index

  {
    "mappings": {
      "dynamic": false,
      "fields": {
        "_id": {
          "type": "string"
        },
        "text": {
          "type": "string"
        },
        "embedding": {
          "type": "knnVector",
          "dimensions": 1536,
          "similarity": "cosine"
        },
        "source": {
          "type": "string"
        },
        "doc_id": {
          "type": "string"
        }
      }
    }
  }

  Feedback Collection Index

  {
    "mappings": {
      "dynamic": false,
      "fields": {
        "prompt": {
          "type": "string"
        },
        "response": {
          "type": "string"
        },
        "text": {
          "type": "string"
        },
        "embedding": {
          "type": "knnVector",
          "dimensions": 1536,
          "similarity": "cosine"
        },
        "feedback": {
          "type": "token"
        }
      }
    }
  }

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.googleDocs","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.memoryMongoDbChat","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas","n8n-nodes-base.telegramTrigger","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas"]

workflow_json_compressed:
  [encoded data, 5824 characters]

metadata_json:
  {"categories":["automation","integration","AI/ML","knowledge management","chatbot"],"complexity":"complex","use_cases":["Build internal AI knowledge assistant","Retrieval-augmented generation (RAG) for product docs","Telegram-based support/chatbot","Collecting RLHF feedback to improve model responses","Storing and searching embeddings in MongoDB vector store"],"estimated_setup_minutes":90,"required_services":["Google Docs","MongoDB Atlas (vector search / Atlas Search)","Telegram Bot API","OpenAI (Embeddings + GPT-4o-mini or similar LLM)","n8n instance (for workflow orchestration)","Public HTTPS endpoint/webhook for Telegram (if not using polling)"],"key_features":["Document ingestion from Google Docs with text splitting","Embedding generation using OpenAI embeddings","Storing embeddings in MongoDB Atlas vector collection with KNN index","Semantic similarity retrieval for RAG","Answer generation via OpenAI GPT-4o-mini with contextual tools integration (product docs, feedback stores)\",\"Telegram bot integration for chat and feedback collection\",\"Reinforcement Learning from Human Feedback (RLHF) loop: capture positive/negative feedback and persist with conversation data\",\"Separate MongoDB collections for docs, feedback, and chat history with provided index templates\",\"Manual trigger for ingestion and automated chat listener workflow"],"target_audience":["Internal support teams","Product specialists","Knowledge managers/owners of documentation repositories (technical or non-technical) \",\"Developers/ML engineers implementing RAG + RLHF integrations"]}


name: 🤖🚚 AI agent for Transportation Orders Management with GPT-4o and Open Route API
author_name: Samir Saci
author_username: samirsaci
categories: []
created_at: 2025-06-05T14:42:16.942Z
updated_at: 2025-06-05T14:42:16.942Z
url: https://n8n.io/workflows/4692
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Tags*: AI Agent, Supply Chain, Logistics, Route Planning, Transportation, GPS API

  Context

  Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting.

  I help companies improve their logistics operations using data, AI, and automation to reduce costs and minimize environmental footprint.

  &gt; Let’s use n8n to automate order management for transportation companies!

  📬 For business inquiries, you can add find me on LinkedIn

  Who is this template for?

  This workflow is designed for small transportation companies and carriers that handle their delivery request by email.



  Two AI Agent nodes and a connection to Openroute Service API are used to parse the content of pickup requests



  The results include driving time and driving distance in a comprehensive and concise reply generated by the second AI Agent.

  How does it work?

  This n8n workflow automates the processing of shipment request emails and enriches them with distance and driving time using the OpenRouteService API.

  📥 Extract structured logistics data (pickup, delivery, contact) using an AI Agent  
  📌 Geocode pickup and delivery addresses into GPS coordinates  
  🚚 Query OpenRouteService using the truck (driving-hgv) profile  
  📏 Get the driving distance (in km) and estimated time (in minutes)  
  📤 Store all data in a connected Google Sheet  
  📧 Send back a professional confirmation email to the customer  

  Steps:
  📩 Trigger the workflow from a new Gmail message  
  🧠 Use the AI Agent to extract structured data from the email  
  📊 Record and enrich shipment details in a Google Sheet  
  🗺️ Geocode addresses into coordinates  
  🚦 Get driving distance & time via OpenRouteService  
  📬 Generate and send back a confirmation email using AI 

  What do I need to get started?

  This workflow requires:

  A Gmail account to receive shipment requests  
  A Google Sheet to log and update shipment info  
  A free OpenRouteService API key  
    👉 Get one here  
  OpenAI API access to use the AI Agent node

  Next Steps

  🗒️ Follow the sticky notes inside the workflow canvas to:

  Plug your Gmail and Google credentials  
  Add your OpenRouteService API key  
  Test by sending a sample email and see the response!


  🎥 Check the Tutorial

  This template was built using n8n v1.93.0  
  Submitted: June 5, 2025

nodes_used:
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workflow_json_compressed:
  [encoded data, 7832 characters]

metadata_json:
  {"categories":["logistics","automation","integration","data processing","AI agent/ML"],"complexity":"medium","use_cases":["Automated processing of shipment/pickup request emails","Extract structured shipment data (pickup/delivery/contact) using AI","Geocode addresses and calculate driving distance and time","Log and update shipment records in Google Sheets","Send professional confirmation emails to customers"],"estimated_setup_minutes":30,"required_services":["Gmail","Google Sheets","OpenRouteService API (free API key)","OpenAI (GPT-4o) / n8n AI Agent","n8n instance"],"key_features":["AI Agent parses unstructured emails into structured shipment data","Geocoding of pickup/delivery addresses to GPS coordinates","Routing lookup using OpenRouteService with truck (driving-hgv) profile","Returns driving distance (km) and estimated time (minutes)","Records and enriches entries in Google Sheets for tracking/audit trail"],"target_audience":["Small transportation companies","Carriers and freight operators","Logistics and supply chain managers/engineers"]}


