# templates

name: Generate & Deliver PDF Invoices from Jotform to Google Drive & Email
author_name: Jitesh Dugar
author_username: jiteshdugar
categories: []
created_at: 2025-10-10T05:04:28.373Z
updated_at: 2025-10-10T05:04:28.373Z
url: https://n8n.io/workflows/9447
scraped_at: 2025-12-24 13:02:41
description:
  Transform your order fulfillment process with complete invoice automation. This workflow automatically generates professional PDF invoices from Jotform orders and delivers them to customers while keeping organized records.

  What This Workflow Does

  ✅ Receives order data from Jotform Trigger  
  ✅ Generates professional HTML invoice with your branding  
  ✅ Converts to PDF using HTML to PDF conversion  
  ✅ Saves invoice to Google Drive for record-keeping  
  ✅ Emails PDF invoice to customer automatically  

  Workflow Steps

  Jotform Trigger - Captures order data when a customer places an order
  Format Invoice Data - Prepares and structures line item data
  Generate HTML Invoice - Creates custom branded HTML invoice
  Generate PDF Invoice - Converts HTML to professional PDF format
  Download File PDF - Prepares PDF for distribution
  Save to Google Drive - Archives invoice for your records
  Email to Customer - Sends invoice PDF directly to customer's inbox

  Requirements

  Jotform account with order form set up Sign up for free here
  PDF generation API key (get yours at pdfmunk.com)
  Google Drive connection for storage
  Email service connection (Gmail, SMTP, etc.)

  Benefits

  Save time** - Eliminate manual invoice creation
  Professional branding** - Customize invoice template to match your brand
  Organized records** - All invoices automatically saved to Google Drive
  Better customer experience** - Instant invoice delivery after order placement
  Scalable** - Handles unlimited orders without additional work

nodes_used:
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workflow_json_compressed:
  [encoded data, 6576 characters]


name: Generate MemeCoin Art with Gemini Flash & NanoBanana and Post to Twitter
author_name: Jay Emp0
author_username: jay-emp0
categories: []
created_at: 2025-10-10T16:24:06.817Z
updated_at: 2025-10-10T16:24:06.817Z
url: https://n8n.io/workflows/9470
scraped_at: 2025-12-24 13:02:45
description:
  🐱 MemeCoin Art Generator - using Gemini Flash NanoBanana & upload to Twitter

  &gt;  Watch the Youtube Tutorial video


  Automatically generates memecoin art and posts it to Twitter (X) powered by Google Gemini, NanoBanana image generation, and n8n automation.

  🧩 Overview

  This workflow creates viral style memecoin images (like Popcat) and posts them directly to Twitter with a witty, Gen Z style tweet.  

  It combines text to image AI, scheduled triggers, and social publishing, all in one seamless flow.

  Workflow flow:
  Define your memecoin mascot (name, description, and base image URL).  
  Generate an AI image prompt and a meme tweet.  
  Feed the base mascot image into Gemini Image Generation API.  
  Render a futuristic memecoin artwork using NanoBanana.  
  Upload the final image and tweet automatically to Twitter.

  🧠 Workflow Diagram

  ⚙️ Key Components

  | Node | Function |
  |------|-----------|
  | Schedule Trigger | Runs automatically at chosen intervals to start meme generation. |
  | Define Memecoin | Defines mascot name, description, and base image URL. |
  | AI Agent | Generates tweet text and creative image prompt using Google Gemini. |
  | Google Gemini Chat Model | Provides trending topic context and meme phrasing. |
  | Get Source Image | Fetches the original mascot image (e.g., Popcat). |
  | Convert Source Image to Base64 | Prepares image for AI based remixing. |
  | Generate Image using NanoBanana | Sends the prompt and base image to Gemini Image API for art generation. |
  | Convert Base64 to PNG | Converts the AI output to an image file. |
  | Upload to Twitter | Uploads generated image to Twitter via media upload API. |
  | Create Tweet | Publishes the tweet with attached image. |

  🪄 How It Works

  1️⃣ Schedule Trigger - starts the automation (e.g., hourly or daily).  
  2️⃣ Define Memecoin - stores your mascot metadata:
        memecoin_name: popcat
     mascot_description: cat with open mouth
     mascot_image: https://i.pinimg.com/736x/9d/05/6b/9d056b5b97c0513a4fc9d9cd93304a05.jpg
     3️⃣ AI Agent - prompts Gemini to:
     Write a short 100 character tweet in Gen Z slang.
     Create an image generation prompt inspired by current meme trends.  
  4️⃣ NanoBanana API - applies your base image + AI prompt to create art.  
  5️⃣ Upload & Tweet - final image gets uploaded and posted automatically.

  🧠 Example Output

  Base Source Image:  


  Generated Image (AI remix):  


  Published Tweet:  


  Example tweet text:
  &gt; Popcat's about to go absolutely wild, gonna moon harder than my last test score! 🚀📈 We up! #Popcat #Memecoin

  🧩 Setup Tutorial

  1️⃣ Prerequisites

  | Tool | Purpose |
  |------|----------|
  | n8n (Cloud or Self hosted) | Workflow automation platform |
  | Google Gemini API Key | For generating tweet and image prompts |
  | Twitter (X) API OAuth1 + OAuth2 | For uploading and posting tweets |

  2️⃣ Import the Workflow

  Download memecoin art generator.json.  
  In n8n, click Import Workflow → From File.  
  Set up and connect credentials:
     Google Gemini API  
     Twitter OAuth  
  (Optional) Adjust Schedule Trigger frequency to your desired posting interval.

  3️⃣ Customize Your MemeCoin

  In the Define Memecoin node, edit these fields to change your meme theme:
  memecoin_name: "doggo"
  mascot_description: "shiba inu in astronaut suit"
  mascot_image: "https://example.com/shiba.jpg"

  That’s it - next cycle will generate your new meme and post it.

  4️⃣ API Notes

  Gemini Image Generation API Docs:**  
    https://ai.google.dev/gemini-api/docs/image-generation#gemini-image-editing
  API Key Portal:**  
    https://aistudio.google.com/api-keys

nodes_used:
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name: Automate HR Recruitment with OpenAI Resume Screening & Interview QnA Generator
author_name: Sandeep Patharkar | www.FastTrackAiMastery.com
author_username: sandy4v
categories: []
created_at: 2025-10-12T16:36:46.448Z
updated_at: 2025-10-12T16:36:46.448Z
url: https://n8n.io/workflows/9528
scraped_at: 2025-12-24 13:02:44
description:
  Build an AI HR Assistant to Screen Resumes and Send Telegram Alerts
  A step-by-step guide to creating a fully automated recruitment pipeline that screens candidates, generates interview questions, and notifies your team.

  This template provides a complete, step-by-step guide to building an AI-powered HR assistant from scratch in n8n. You will learn how to connect a web form to an intelligent screening agent that reads resumes, evaluates candidates against your job criteria, and prepares unique interview questions for the most promising applicants.



  | Services Used                               | Features                                                                   |
  | :---------------------------------------------- | :----------------------------------------------------------------------------- |
  | 🤖 OpenAI / LangChain                         | Uses AI Agents to screen, score, and analyze candidates.                       |
  | 📄 Google Drive & Google Sheets               | Stores resumes and manages a database of open positions and applicants.        |
  | 📥 n8n Form Trigger                           | Provides a public-facing web form to capture applications.                     |
  | 💬 Telegram                                   | Sends real-time alerts to the hiring team for qualified candidates.            |

  How It Works ⚙️

  📥 Application Submitted: The workflow starts when a candidate fills out the n8n Form Trigger with their details and uploads their CV.
  📂 File Processing: The CV is automatically uploaded to a specific Google Drive folder for record-keeping, and the Extract from File node reads its text content.
  🧠 AI Screening Agent: A LangChain Agent analyzes the resume text. It uses the Google Sheets Tool to look up the requirements for the applied role, then scores the candidate and decides if they should be shortlisted.
  📊 Log Results: The agent's decision (name, score, shortlisted status) is logged in your master "Applications" Google Sheet.
  ✅ Qualification Check: An IF node checks if the candidate was shortlisted.
  ❓ AI Question Generator: If shortlisted, a second LangChain Agent generates three unique, relevant interview questions based on the candidate's resume and the job description.
  ✍️ Update Sheet: The generated questions are added to the candidate's row in the Google Sheet.
  🔔 Notify Team: A final alert is sent via Telegram to notify the HR team that a new candidate has been qualified and is ready for review.

  🛠️ How to Build This Workflow

  Follow these steps to build the recruitment assistant from a blank canvas.

  Step 1: Set Up the Application Intake
  Add a Form Trigger node. Configure it with fields for Name, Email, Phone Number, a File Upload for the CV, and a Dropdown for the "Job Role".
  Connect a Google Drive node. Set the Operation to Upload and connect your credentials. Set it to upload the CV file from the Form Trigger into a specific folder.
  Add an Extract from File node. Set it to extract text from the PDF CV file provided by the trigger.

  Step 2: Build the AI Screening Agent
  Add a Langchain Agent node. This will be your main screening agent.
  In its prompt, instruct the AI to act as a resume screener. Tell it to use the input text from the Extract from File node and the tools you will provide to score and shortlist candidates.
  Add an OpenAI Chat Model node and connect it to the Agent's Language Model input.
  Add a Google Sheets Tool node. Point it to a sheet with your open positions and their requirements. Connect this to the Agent's Tool input.
  Add a Structured Output Parser node and define the JSON structure you want the agent to return (e.g., candidate_name, score, shortlisted). Connect this to the Agent's Output Parser input.

  Step 3: Log Results & Check for a Match
  Connect a Google Sheets node after the Agent. Set its operation to Append or Update. Use it to add the structured output from the agent into your main "Applications" sheet.
  Add an IF node. Set the condition to continue only if the shortlisted field equals "yes".

  Step 4: Generate Interview Questions
  On the 'true' path of the IF node, add a second Langchain Agent node.
  Write a prompt telling this agent to generate 3 interview questions based on the candidate's resume and the job requirements.
  Connect the same OpenAI Model and Google Sheets Tool to this agent.
  Add another Google Sheets node. Set it to Update the existing row for the candidate, adding the newly generated questions.

  💬 Need Help or Want to Learn More?

  Join my Skool community for n8n + AI automation tutorials, live Q&A sessions, and exclusive workflows:  
  👉 https://www.skool.com/n8n-ai-automation-champions

  Template Author: Sandeep Patharkar  
  Category: Website Chatbots / AI Automation  
  Difficulty: Beginner  
  Estimated Setup Time: ⏱️ 15 minutes

nodes_used:
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name: Outlook Inbox Tamer: GPT-4.1 Powered Categorization, Auto Replies & Team Alerts
author_name: Sandeep Patharkar | www.FastTrackAiMastery.com
author_username: sandy4v
categories: []
created_at: 2025-10-12T16:47:10.185Z
updated_at: 2025-10-12T16:47:10.185Z
url: https://n8n.io/workflows/9529
scraped_at: 2025-12-24 13:02:45
description:
  Outlook Inbox Tamer: AI-Powered Categorization, Auto Replies & Team Alerts

  This workflow automatically classifies and routes incoming Outlook emails into smart categories using n8n + OpenAI GPT-4.1-mini.  
  It helps professionals and teams stay organized by intelligently sorting and responding to high-priority messages, customer support emails, promotions, and finance-related messages — all without manual effort.

  🧠 Who’s It For
  Professionals or teams overwhelmed by email volume.  
  Customer support, operations, or finance teams needing real-time triage.  
  Anyone who wants AI to help manage and prioritize their Outlook inbox.

  ⚙️ How It Works
  Microsoft Outlook Trigger monitors your inbox for new emails.  
  OpenAI GPT-4.1-mini analyzes each email and classifies it as one of:  
     High_Priority  
     Customer_Support  
     Promotions  
     Finance/Billing  
  Routing node moves emails to matching Outlook folders.  
  AI-generated replies and Telegram notifications keep the right team informed instantly.  
  (Optional) Use Google Sheets + Manual Trigger to test with sample data before going live.

  🛠️ Requirements
  Outlook account connected via Microsoft Outlook OAuth2.  
  OpenAI API key** (set up in n8n credentials).  
  (Optional) Telegram bot token for team alerts.  
  (Optional) Google Sheets for test emails.

  🔧 How to Set Up
  Import the workflow into your n8n instance.  
  Add credentials for:
     Microsoft Outlook  
     OpenAI  
     Telegram (optional)  
  Deploy and activate the workflow.  
  Start sending or receiving emails — watch them get auto-classified and organized!

  🧩 How to Customize
  Update the system prompt in the Email_Classifier_Agent to add more categories (like HR, Legal, etc.).  
  Change Telegram recipients for alerts.  
  Extend the workflow to post classified data into Notion, Slack, or CRM.

  📘 Example Use Case
  An AI agent monitors your Outlook inbox, classifies incoming emails in real time, moves them to their respective folders, creates response drafts, and alerts your team instantly through Telegram.

  💬 Connect with the Creator
  👋 Created by Sandeep Patharkar  
  💼 Connect on LinkedIn  
  🌐 Join my Skool community for n8n + AI automation tutorials, live Q&As, and exclusive workflow templates.

  Category: Email Automation / AI Productivity  
  Difficulty: Intermediate  
  Estimated Setup Time: ⏱️ 10–15 minutes

nodes_used:
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name: Create Deepfake Videos by Swapping Faces with Fal.ai Wan 2.2 and AWS S3
author_name: Sandeep Patharkar | www.FastTrackAiMastery.com
author_username: sandy4v
categories: []
created_at: 2025-10-12T21:55:55.239Z
updated_at: 2025-10-12T21:55:55.239Z
url: https://n8n.io/workflows/9541
scraped_at: 2025-12-24 13:02:45
description:
  Animate Any Face into a Video with Fal.ai
  Create stunning deepfake-style videos automatically by swapping a face from an image onto a source video.

  This workflow provides a powerful, automated pipeline to perform video face-swapping using the Fal.ai API. It's designed to handle the entire asynchronous process: accepting a source video and a target face image, uploading them to cloud storage, initiating the AI job, polling for completion, and retrieving the final, rendered video.

  | Services Used | Features |
  | :--- | :--- |
  | 🤖 Fal.ai | Leverages the powerful Wan 2.2 model for high-quality face animation. |
  | ☁️ AWS S3 | Uses enterprise-grade cloud storage for reliable public file hosting. |
  | 🔄 Polling Loop | Intelligently waits for the asynchronous AI job to complete before proceeding. |
  | 📥 n8n Form Trigger | Provides a simple UI to upload your source image and video. |

  How It Works ⚙️

  📥 Get User Input: The workflow starts when you upload a source video and a face image via the n8n Form Trigger.
  ☁️ Upload to Cloud: Both files are automatically uploaded to a specified AWS S3 bucket to generate the publicly accessible URLs required by the AI model.
  🚀 Start AI Job: The public URLs for the video and image are sent in an HTTP Request to the Fal.ai API, which starts the asynchronous face animation process and returns a request_id.
  ⏳ Wait & Check: The workflow enters a polling loop. It Waits for one minute, then makes another HTTP Request to the Fal.ai status endpoint using the request_id.
  ✅ Check for Completion: An IF node checks if the job status is COMPLETED. If not, the workflow loops back to the Wait node.
  🎬 Retrieve Final Video: Once the job is complete, the workflow makes a final HTTP Request to fetch the finished animated video.

  🛠️ How to Set Up

  🔑 Set Up Fal.ai Credentials: Get your API Key from Fal.ai. In n8n, go to Credentials, add a new Header Auth credential, and save your key. Connect this credential to all three HTTP Request nodes in the workflow.
  ☁️ Configure AWS S3: Add your AWS credentials in n8n. In the two AWS S3 nodes (Upload Video1 and Upload Image1), update the Bucket Name parameter to your own S3 bucket. Ensure your bucket permissions allow for public reads.
  ▶️ Activate and Run: Activate the workflow. Open the Form Trigger URL from the n8n editor, upload your files, and submit. The final video will be available in the execution log of the Get Final Video node.

  Requirements

  An active Fal.ai account and API key.
  An AWS account with an S3 bucket configured for public access.
  Alternative Storage:* For a personal setup, you can replace the AWS S3 nodes with *Cloudinary** nodes. Just ensure the output is a public URL.

  💬 Need Help or Want to Learn More?

  Join my Skool community for n8n + AI automation tutorials, live Q&A sessions, and exclusive workflows:
      👉 https://www.skool.com/n8n-ai-automation-champions

  Template Author: Sandeep Patharkar  
  Category: Content Generation / Content Marketing
  Difficulty: Intermediate  
  Estimated Setup Time: ⏱️ 20 minutes

nodes_used:
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name: Generate Complete Database Schemas with Claude for SQL Databases
author_name: Evervise
author_username: evervise
categories: []
created_at: 2025-10-13T00:27:53.140Z
updated_at: 2025-10-13T00:27:53.140Z
url: https://n8n.io/workflows/9544
scraped_at: 2025-12-24 13:02:41
description:
  Transform database design from weeks to minutes with this intelligent multi-agent system. Perfect for agencies, consultancies, and SaaS companies offering database architecture as a lead magnet or service.

  🤖 4 Specialized AI Agents:
  Agent 1 (Architect):** Designs complete schema with tables, relationships, indexes
  Agent 2 (Reviewer):** Validates design for performance, security, scalability
  Agent 3 (Optimizer):** Adds advanced features and scores the design (0-100)
  Agent 4 (SQL Generator):** Creates production-ready migration scripts

  🔄 Smart Quality Loop:
  Automatically retries up to 3 times if score falls below B grade, feeding previous feedback to improve the design iteratively.

  ✨ What You Get:
  Complete database schema (JSON)
  Comprehensive score card with letter grade
  Review feedback with severity levels (Critical/High/Medium/Low)
  Production-ready SQL migration script
  Optional auto-execution in PostgreSQL/MySQL
  Iteration count and optimization recommendations

  💼 Perfect For:
  Digital agencies offering database design services
  SaaS companies needing rapid prototyping
  Consultancies creating lead magnets
  Developers modernizing legacy systems
  Startups validating data models

  🎯 Use as Lead Magnet:
  Offer free database blueprints to capture leads, then upsell implementation, custom automations, and ongoing optimization services.

  ⚙️ Technical Highlights:
  Optimized temperature settings per agent (0.1-0.5)
  Claude Sonnet 4.5 for maximum quality
  Structured JSON output for easy integration
  Error handling and graceful degradation
  Execution time: 60-90 seconds average
  Cost: ~$0.15-0.30 per run

  Use Cases

  Agency Lead Magnet
     Capture leads by offering free database architecture reviews and blueprints

  Rapid Prototyping
     Quickly generate database schemas for MVP development and validation

  Legacy System Modernization
     Help companies redesign outdated database structures with modern best practices

  Technical Consulting
     Provide instant database assessments and recommendations to clients

  Educational Tool
     Teach database design principles through AI-generated examples and feedback

  Pre-Sales Tool
     Demonstrate technical expertise to prospects before engagement

  Key Features

  ✅ Multi-agent AI collaboration with specialized roles
  ✅ Automatic quality control and iterative improvement (max 3 retries)
  ✅ Support for PostgreSQL, MySQL, MSSQL, MariaDB
  ✅ Production-ready SQL script generation
  ✅ Comprehensive scoring system (Schema/Performance/Scalability/Security)
  ✅ Optional automatic SQL execution
  ✅ Detailed feedback with actionable recommendations
  ✅ Customizable form fields for different industries
  ✅ Error handling and graceful failures
  ✅ Complete audit trail of all agent decisions

  Setup Instructions

  PREREQUISITES:
  Anthropic API key (Claude Sonnet 4.5 access)
  PostgreSQL/MySQL database (optional, for auto-execution)
  n8n version 1.0+ with LangChain nodes

  CONFIGURATION STEPS:

  Import the workflow JSON into your n8n instance

  Configure Anthropic API credentials:
     Add your Anthropic API key in n8n credentials
     Connect all 4 AI model nodes to your credential

  (Optional) Configure database connection:
     In "Execute SQL in PostgreSQL" node, add your database credentials
     Use a TEST/SANDBOX database, never production
     Or disable this node if you prefer manual execution

  Customize the form (optional):
     Edit form fields in "On form submission" node
     Add industry-specific questions
     Adjust required fields based on your needs

  Test the workflow:
     Use the form URL to submit a test request
     Check execution time and quality
     Verify all agents are responding correctly

  Customize agent prompts (optional):
     Adjust system messages for industry-specific requirements
     Modify scoring criteria in Agent 3
     Add custom validation rules in Agent 2

  Deploy:
     Share the form URL as your lead magnet
     Embed in website or landing pages
     Set up email notifications for submissions

  COST CONSIDERATIONS:
  Each execution costs ~$0.15-0.30 in API calls
  Failed attempts (retries) increase cost
  Consider rate limiting for public forms

  Requirements

  REQUIRED:
  Anthropic API Key (Claude access)
  n8n version 1.0+
  LangChain nodes enabled

  OPTIONAL:
  PostgreSQL/MySQL database connection (for auto-execution)
  Email service (for result delivery)
  CRM integration (for lead capture)

  Tags

  #ai-agents #database-design #postgresql #mysql #lead-generation #automation #langchain #claude #schema-design #multi-agent #consulting-tool #saas-tool #development #code-generation #sql-generator

  📖 Website: https://evervise.ai/
  ✨ Support: mark.marin@evervise.com

  N8N Link

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name: Landing Page Analysis & Optimization with Claude's 4-Agent AI System
author_name: Evervise
author_username: evervise
categories: []
created_at: 2025-10-13T00:49:56.638Z
updated_at: 2025-10-13T00:49:56.638Z
url: https://n8n.io/workflows/9545
scraped_at: 2025-12-24 13:02:42
description:
  🎯 AI Landing Page Analyzer & Optimizer

  Transform your landing page audits into a powerful lead generation machine with this professional n8n workflow powered by 4 specialized AI agents.

  What It Does

  This workflow analyzes any landing page and delivers a comprehensive, $2,000-value audit report in under 90 seconds. Perfect for agencies, consultants, and SaaS companies looking to generate high-quality leads while showcasing their expertise.

  🤖 Four Specialized AI Agents

  Design Critic - Analyzes UX/UI, visual hierarchy, CTA placement, mobile responsiveness, and trust signals
  Copywriter - Reviews messaging, headlines, value propositions, and emotional triggers
  SEO Specialist - Audits technical SEO, meta tags, heading structure, and performance indicators
  Growth Strategist - Synthesizes all findings, assigns an A-F grade, and creates prioritized action plans

  ✨ Key Features

  Comprehensive Scoring**: 6-dimension scorecard with detailed justifications
  Actionable Insights**: Top 5 priorities ranked by impact vs. effort
  Conversion Lift Estimates**: Conservative, realistic, and optimistic projections
  Beautiful HTML Reports**: Professional email with all analyses, branded for your business
  Natural Upsell Path**: Built-in CTA for paid optimization services
  Fast Delivery**: Complete analysis in 60-90 seconds

  📊 What Gets Analyzed

  Design & UX
  Visual hierarchy and layout structure
  CTA design, placement, and effectiveness
  Color scheme and whitespace usage
  Trust signals and social proof
  Mobile responsiveness indicators

  Copywriting
  Headline impact and hook effectiveness
  Value proposition clarity
  Benefits vs. features balance
  Emotional triggers and persuasion
  CTA copy strength and action orientation

  SEO & Technical
  Title tag and meta description optimization
  Heading structure (H1, H2 hierarchy)
  Image optimization and alt tags
  Mobile-friendliness
  Analytics tracking setup
  Page speed indicators

  Strategic Overview
  Overall grade (A+ to F) with detailed explanation
  Comprehensive scorecard across all dimensions
  Prioritized action items by ROI
  Estimated conversion lift potential
  Strategic recommendations and next steps

  💼 Perfect For

  Digital Marketing Agencies**: Offer free audits to generate leads
  Freelance Consultants**: Showcase expertise and attract clients
  SaaS Companies**: Lead magnet for conversion optimization tools
  Web Development Agencies**: Pre-sales qualification and demonstrations
  CRO Specialists**: Automated initial assessments

  📋 What You Need

  Required
  n8n instance (self-hosted or cloud)
  Anthropic API key (Claude Sonnet 4.5)
  Gmail account for sending reports (or any SMTP provider)

  Optional Enhancements
  Screenshot API (UrlBox, Puppeteer) for visual captures
  Google PageSpeed Insights API for performance testing
  CRM integration (HubSpot, Salesforce, Pipedrive)
  Slack notifications for lead alerts
  Calendar booking integration (Calendly)

  ⚙️ Technical Details

  AI Model**: Claude Sonnet 4.5 (4 separate agents)
  Average Runtime**: 60-90 seconds
  Cost Per Analysis**: ~$0.15-0.25 (API costs)
  Form Fields**: 6 (landing page URL, industry, goal, conversion rate, frustration, email)
  Output**: Beautiful HTML email report with comprehensive analysis

  🎨 Customization Options

  The workflow includes detailed documentation and is fully customizable:

  Adjust agent prompts for your specific niche
  Modify scoring criteria and thresholds
  Customize email branding and design
  Add/remove form fields
  Integrate with your CRM
  Segment responses by score (different CTAs for different grades)

  📈 Expected Results

  Lead Quality**: High (users actively seeking optimization)
  Conversion Rate**: 15-30% of audit recipients book calls
  Time Saved**: 2-3 hours of manual analysis per audit
  Perceived Value**: $2,000+ professional audit

  🔧 Setup Difficulty

  Intermediate - Requires basic n8n knowledge and API key setup

  Setup Steps
  Import workflow to n8n
  Add Anthropic API credentials
  Configure Gmail/SMTP credentials
  Customize form and email branding
  Test with sample landing page
  Deploy form on your website

  📚 Included Documentation

  Comprehensive sticky notes explaining each component
  Setup instructions and prerequisites
  Customization guide
  Monetization strategy breakdown
  Performance optimization tips
  Enhancement ideas for v2

  🌟 Use Cases

  Lead Magnet: Embed form on your website to capture qualified leads
  Sales Tool: Use during discovery calls to demonstrate value
  Content Marketing: Offer audits in LinkedIn posts, email campaigns
  Partner Program: Provide white-labeled audits to partners
  Upsell Sequence: Follow up with paid optimization services

  ⚡ Why This Workflow?

  Unlike simple template-based audits, this workflow uses real AI intelligence to provide nuanced, contextual insights. Each analysis is unique and considers:

  Industry-specific best practices
  Stated business goals
  Current pain points
  Competitive landscape
  User's experience level

  The result? Reports that feel hand-crafted by experts, not generic checklists.

  🤝 Support

  📖 Website: https://evervise.ai/
  ✨ Support: mark.marin@evervise.com

  N8N Link

  📊 Version History

  v1.0** - Initial release with 4-agent analysis pipeline
  Coming soon: Screenshot capture, competitor comparison, visual mockups

  Tags

  lead-generation marketing-automation ai-agents conversion-optimization landing-pages anthropic claude audit seo copywriting design-analysis lead-magnet

  Ready to turn landing page audits into a lead generation machine? Import this workflow and start attracting high-quality clients today.

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name: Generate Business Automation Opportunities & ROI Reports with Claude AI
author_name: Evervise
author_username: evervise
categories: []
created_at: 2025-10-13T01:00:14.525Z
updated_at: 2025-10-13T01:00:14.525Z
url: https://n8n.io/workflows/9546
scraped_at: 2025-12-24 13:02:41
description:
  🤖 AI Business Automation Opportunity Finder

  Turn automation audits into high-ticket sales with this ROI-focused n8n workflow powered by 4 specialized AI agents that identify and quantify automation opportunities in any business.

  What It Does

  This workflow analyzes any business and delivers a comprehensive automation blueprint with concrete ROI calculations in under 60 seconds. Perfect for agencies, consultants, and automation experts looking to generate qualified leads and close high-value deals.

  Unlike generic automation advice, this delivers personalized, quantified opportunities ranked by return on investment - making it incredibly easy for prospects to say yes.

  🤖 Four Specialized AI Agents

  Business Analyst - Deep analysis of business model, workflows, pain points, tech stack, and scalability challenges
  Process Mapper - Maps all repetitive processes, calculates time waste, identifies bottlenecks across the entire operation
  Automation Architect - Designs 15+ specific automation solutions with tools, complexity ratings, and implementation steps
  ROI Calculator - Calculates detailed ROI for each automation, ranks top 10, creates 90-day implementation roadmap

  ✨ Key Features

  Concrete Dollar Savings**: Every automation shows exact time saved, labor cost saved, and payback period
  Top 10 Ranked by ROI**: Opportunities prioritized by impact vs. effort with detailed financial analysis
  90-Day Implementation Roadmap**: Month-by-month plan showing progressive savings milestones
  Comprehensive Process Mapping**: Identifies inefficiencies they didn't even mention
  Tool-Specific Recommendations**: Exact tools and platforms needed (n8n, Zapier, Make, etc.)
  Beautiful HTML Reports**: Professional, conversion-focused email with 3-tier pricing built in
  Multiple CTAs**: Strategically placed conversion points throughout the report

  📊 What Gets Analyzed

  Business Analysis
  Business model and revenue streams
  Operational workflows and processes
  Current tech stack assessment
  Team capacity and resource allocation
  Growth stage and scalability blockers
  Industry-specific automation patterns

  Process Mapping
  Comprehensive workflow documentation
  Time waste analysis (hours per month)
  Bottleneck identification
  Process dependencies and integration opportunities
  Quick win vs. strategic project categorization

  Automation Architecture
  For each of 15+ automation opportunities:
  Clear description of what it automates
  Specific tools required
  Step-by-step implementation flow
  Complexity rating (Easy/Medium/Hard)
  Prerequisites and requirements
  Additional benefits beyond time savings
  Real-world use case examples

  ROI Calculations
  For each automation:
  Time saved per week/month/year
  Labor cost savings (calculated from team size/industry)
  One-time implementation cost
  Ongoing monthly costs
  Payback period in months
  12-month net savings
  ROI percentage
  Priority score (0-10)

  💼 Perfect For

  Automation Agencies**: High-value lead magnet that pre-sells your services
  Business Consultants**: Demonstrate ROI before engagement
  No-Code Developers**: Show concrete value of your expertise
  Digital Transformation Consultants**: Quantify the opportunity
  SaaS Companies**: Lead gen for automation/workflow tools
  Freelancers**: Land bigger clients with data-driven proposals

  🚀 Why This Converts Better Than Other Lead Magnets

  Traditional Lead Magnets:
  Generic advice ("You should automate")
  Subjective benefits ("Save time")
  No clear next steps
  Conversion rate: 5-10%

  This Workflow:
  Specific to their business** (personalized analysis)
  Quantified in dollars** ($50K+ annual savings)
  Prioritized action plan** (top 10 ranked by ROI)
  Clear implementation path** (90-day roadmap)
  Conversion rate: 20-30%** to strategy call
  40-50% of calls close** to paid engagement

  📈 Expected Business Results

  Per 100 Form Submissions:
  25-30 strategy calls booked** (25-30% conversion)
  10-15 deals closed** (40-50% call-to-close rate)
  $12K-18K in initial revenue** (mix of Tier 1 & 2)
  2-4 retainer clients** ($30K-60K annual value)
  Total potential: $42K-78K** from 100 leads

  Why It Works:
  Self-qualifying**: Detailed form filters serious prospects
  Pre-sold**: They see the value before the call
  ROI-focused**: Speaks CFO language (dollars, not features)
  Urgency**: Shows money being wasted daily
  Social proof**: Built-in testimonials and case studies

  📋 What You Need

  Required
  n8n instance (self-hosted or cloud)
  Anthropic API key (Claude Sonnet 4.5)
  Gmail account or SMTP provider

  Optional Enhancements
  CRM integration (HubSpot, Salesforce, Pipedrive)
  Slack notifications for high-value leads
  Calendly for automatic call booking
  Zapier/Make for additional workflows
  Analytics tracking (Mixpanel, Segment)

  ⚙️ Technical Details

  AI Model**: Claude Sonnet 4.5 (4 sequential agents)
  Average Runtime**: 50-70 seconds
  Cost Per Analysis**: ~$0.20-0.30
  Form Fields**: 9 (business description, industry, team size, tasks, tools, bottleneck, revenue, email, name)
  Output**: Comprehensive HTML email with all analyses, pricing, and CTAs

  🎨 Customization Options

  The workflow is fully customizable and includes detailed documentation:

  Adjust ROI calculation parameters (labor rates by industry)
  Modify agent prompts for specific niches
  Customize pricing tiers and packages
  Add/remove form fields
  White-label the entire report
  Integrate with your CRM/marketing stack
  Segment responses by company size or revenue
  Add video walkthroughs or personalized messages
  Create industry-specific versions

  📊 Form Fields Explained

  The 9-field form is strategically designed to gather intelligence:

  Business Description (textarea): Core operations and offerings
  Industry/Niche (text): Context for automation patterns
  Team Size (dropdown): Affects ROI calculations and tool recommendations
  Repetitive Tasks (textarea): Gold mine for automation opportunities
  Current Tools (textarea): Integration points and tech stack assessment
  Biggest Bottleneck (textarea): Primary pain point for targeting
  Monthly Revenue (optional dropdown): For accurate ROI estimates and lead scoring
  Email (required): For report delivery
  Name (required): For personalization

  🔧 Setup Difficulty

  Basic - Requires basic n8n knowledge and API configuration

  Setup Steps
  Import workflow JSON to n8n
  Add Anthropic API credentials
  Configure Gmail/SMTP credentials
  Customize branding and pricing in email template
  Test with sample business scenarios
  Deploy form on your website
  Set up follow-up sequences (recommended)

  📚 Included Documentation

  Comprehensive sticky notes** for every component
  Setup instructions** with prerequisites
  Customization guide** for different industries
  Pricing strategy** breakdown and alternatives
  Conversion optimization** tips
  Follow-up sequence** recommendations
  Sales script** suggestions for strategy calls
  Marketing promotion** ideas

  🌟 Advanced Use Cases

  1. Lead Magnet
  Embed on website to capture qualified automation leads continuously

  2. Discovery Tool
  Use during sales calls to demonstrate immediate value and build credibility

  3. Content Marketing
  Offer in LinkedIn posts, email campaigns, YouTube videos for viral growth

  4. Partner Program
  White-label for partners/affiliates to generate leads in their networks

  5. Upsell Sequence
  For existing clients, identify additional automation opportunities

  6. Industry Templates
  Create versions for specific industries (real estate, e-commerce, agencies)

  7. Competitive Intelligence
  Analyze competitor operations and position your services

  ⚡ Why This Workflow Stands Out

  Compared to Generic Automation Audits:
  ✅ Quantified in dollars vs. vague "save time" claims
  ✅ Personalized to their business vs. generic templates
  ✅ Prioritized by ROI vs. random feature lists
  ✅ Actionable roadmap vs. overwhelming possibilities
  ✅ Tool-specific vs. theoretical concepts

  Compared to Manual Analysis:
  ✅ 60 seconds vs. 2-3 hours of consultant time
  ✅ $0.25 cost vs. $300-500 in labor
  ✅ Consistent quality vs. variable analyst experience
  ✅ Scalable vs. bottlenecked by human capacity
  ✅ 24/7 available vs. business hours only

  🤝 Support & Community

  📖 Website: https://evervise.ai/
  ✨ Support: mark.marin@evervise.com

  N8N Link

  🎁 Bonus Resources Included

  Follow-up email sequence** (3 emails over 10 days)
  Sales call script** for strategy calls
  Objection handling** guide
  Pricing calculator** spreadsheet
  Marketing assets** (social media templates)
  Case study template** for testimonials

  Tags

  automation lead-generation roi-calculator business-analysis process-mapping ai-agents anthropic claude workflow-automation business-consulting no-code n8n-workflows high-ticket-sales conversion-optimization saas-tools

  Ready to turn automation audits into recurring revenue? Import this workflow and start attracting qualified leads who can see the exact dollar value you provide before they even talk to you.

  Average user results: $42K-78K revenue from first 100 form submissions.

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name: Convert Fathom meeting transcripts to formatted Google Docs with AI summaries
author_name: Dean Pike
author_username: deanjp
categories: []
created_at: 2025-10-13T04:00:31.144Z
updated_at: 2025-10-13T04:00:31.144Z
url: https://n8n.io/workflows/9549
scraped_at: 2025-12-24 13:02:41
description:
  Transcript → AI Analysis → Formatted Doc

  This workflow automatically converts Fathom meeting transcripts into beautifully formatted Google Docs with AI-generated summaries, key points, decisions, and action items.

  Good to know
    Works fully with Fathom free account
    Webhook responds immediately to prevent Fathom timeout and duplicate triggers
    Validates transcript quality (3+ conversation turns) before AI processing to save costs
    Uses Google Gemini API (generous free tier and rate limits, typically enough to avoid paying for API requests, but check latest pricing at Google AI Pricing)
    Creates temporary HTML file that's auto-deleted after conversion

  Who's it for
    Individuals or teams using Fathom for meetings who want more control and flexibility with their AI meeting analysis and storage independently of Fathom, as well as automatic, formatted documentation without manual note-taking. Perfect for recurring syncs, client meetings, or interview debriefs.

  How it works
    Fathom webhook triggers when meeting ends and sends transcript data
    Validates transcript has meaningful conversation (3+ turns)
    Google Gemini AI analyzes transcript and generates structured summary (key points, decisions, actions, next steps)
    Creates formatted HTML with proper styling
    Uploads to Google Drive and converts to native Google Doc
    Reduces page margins for readability and deletes temporary HTML file

  Requirements
    Fathom account with API webhook access (available on free tier)
    Google Drive account (OAuth2)
    Google Docs account (OAuth2)
    Google Gemini API key (Get free key here)

  How to set up
    Add credentials: Google Drive OAuth2, Google Docs OAuth2, Google Gemini API
    Copy the webhook URL from the Get Fathom Meeting webhook node (Test URL first, change to Production URL when ready)
    In Fathom: Settings → API Access → Add → Add webhook URL and select all events including "Transcript"
    Test with a short meeting, verify Google Doc appears in Drive
    Activate workflow

  Customizing this workflow
    Change save location: Edit "Upload File as HTML" node → update "Parent Folder"
    Modify AI output: Edit "AI Meeting Analysis" node → customize the prompt to add/remove sections (e.g., risks, follow-ups, sentiment, etc)
    Adjust document margins: Edit "Reduce Page Margins" node → change margin pixel values
    Add notifications: E.g. add Slack/Email node after "Convert to Google Doc" to notify team when summary is ready

  Quick Troubleshooting
    "Transcript Present?" fails: Fathom must send transcript_merged with 3+ conversation turns (i.e. only send to Gemini for analysis if there's a genuine transcript)
    HTML as plain text: Check "Convert to Google Doc" uses POST to /copy endpoint
    401/403 errors: Re-authorize Google credentials
    Inadequate meeting notes: Edit prompts in "AI Meeting Analysis" node
  Sample File and Storage Output
  Google Doc meeting notes - sample
  Google Drive sample folder output:

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name: Automatically Send WhatsApp Discount Codes to Shopify Customers Using Rapiwa
author_name: Rapiwa
author_username: rapiwa
categories: []
created_at: 2025-10-13T07:24:06.233Z
updated_at: 2025-10-13T07:24:06.233Z
url: https://n8n.io/workflows/9560
scraped_at: 2025-12-24 13:02:46
description:
  Automatically Send WhatsApp Discount Codes to Shopify Customers Using Rapiwa

  Who is this for?
  This n8n workflow automatically sends WhatsApp promotional messages to top customers whenever a new discount code is created in Shopify. It’s perfect for store owners, marketers, sales teams, or support agents who want to engage their best customers effortlessly. The workflow fetches customer data, filters high-spending customers, verifies their WhatsApp numbers using the Rapiwa API, sends discount messages to verified contacts, and logs all activity in Google Sheets. Designed for non-technical users who don’t use the official WhatsApp Business API, this automation simplifies customer outreach and tracking without any manual work.

  What this Workflow Does
  This n8n workflow connects with a Google Sheet that contains a list of contacts. It reads rows marked for processing, cleans the phone numbers, checks their validity using Rapiwa's WhatsApp validation API, sends WhatsApp messages to valid numbers, and updates the status of each row accordingly.

  Key Features
  Runs Every 5 Minutes**: Automatically triggers the workflow
  Google Sheets Integration**: Reads and writes data from a specific sheet
  Phone Number Validation**: Confirms if a WhatsApp number is active via Rapiwa API
  Message Sending**: Sends a message using Rapiwa's /send-message endpoint
  Status Update**: Sheet is updated with success or failure status
  Safe API Usage**: Delays added between requests to prevent rate limits
  Batch Limit**: Processes max 60 rows per cycle
  Conditional Checks**: Skips rows without a "check" value

  Requirements
  A Google Sheet with necessary columns
  Rapiwa account** with active subscription (you can free 200 message)
  Your WhatsApp number connected to Rapiwa
  Valid Bearer Token
  n8n Instance** (self-hosted or cloud)
    Google Sheets node configured
    HTTP Request node access

  How to Use
  Step-by-Step Setup

  Webhook
     Receives Shopify Webhook (discount creation) via HTTP POST request.  
  This is triggered when a discount is created in your Shopify store.

  Configure Google Sheets in n8n
     Use the Google Sheets node with OAuth2 access

  Get Rapiwa API Token
     Create an account on Rapiwa
     Connect your WhatsApp number
     Copy your Bearer Token from the Rapiwa dashboard

  Set Up HTTP Request Nodes
     Validate number via: https://app.rapiwa.com/api/verify-whatsapp
     Send message via: https://app.rapiwa.com/api/send-message
     Add your bearer token to the headers

  Google Sheet Column Structure
  A Google Sheet** formatted like this ➤ Sample


  | discount_code   | created_at                | shop_domain             | name           | number        | verify     | status   |
  | -------------------------------------------- | ------- | ------------------------- | ----------------------- | -------------- | ------------- | ---------- | -------- |
  | V8ZGVRDFP5TB | 2025-09-25T05:26:40-04:00 | your_shop_domain | Abdul Mannan    | 8801322827798| unverified | not sent |
  | V8ZGVRDFP5TB | 2025-09-25T05:26:40-04:00 | your_shop_domain | Abdul Mannan         | 8801322827799| verified   | sent     |

  Support & Help
  Rapiwa Website:** https://rapiwa.com
  WhatsApp**: Chat on WhatsApp
  Discord**: SpaGreen Community
  Facebook Group**: SpaGreen Support
  Website**: https://spagreen.net
  Developer Portfolio**: Codecanyon SpaGreen

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name: Generate AI Videos with Sora2 Pro, Save to Google Drive and Upload to YouTube
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-10-13T14:01:53.749Z
updated_at: 2025-10-13T14:01:53.749Z
url: https://n8n.io/workflows/9576
scraped_at: 2025-12-24 13:02:41
description:
  This workflow automates the entire process of creating, managing, and publishing AI-generated videos using OpenAI Sora2 Pro, Google Sheets, Google Drive, and YouTube.

  Advantages

  ✅ Fully Automated Video Pipeline
  From idea to YouTube publication with zero manual intervention after setup.

  ✅ Centralized Control via Google Sheets
  Simple spreadsheet interface — no need to use APIs or dashboards directly.

  ✅ AI-Powered Video Creation
  Uses OpenAI Sora2 Pro for generating professional-quality videos from text prompts.

  ✅ SEO-Optimized Titles with GPT-5
  Automatically creates catchy, keyword-rich titles optimized for YouTube engagement.

  ✅ Cloud Integration
  Seamless use of Google Drive for file management and YouTube for publishing.

  ✅ Scalable and Repeatable
  Can handle multiple videos in sequence, triggered manually or at regular intervals.

  ✅ Error-Resilient and Transparent
  Uses conditional checks (“Completed?” node) and real-time updates in Google Sheets to ensure reliability and visibility.

  How it Works

  This workflow automates the entire process of generating AI videos and publishing them to YouTube, using a Google Sheet as the central control panel.

  Trigger & Data Fetch: The workflow is triggered either manually or on a schedule. It starts by reading a specific Google Sheet to find new video requests. A new request is identified as a row where the "PROMPT" and "DURATION" columns are filled, but the "VIDEO" column is empty.
  AI Video Generation: For each new request, it takes the prompt and duration, then sends a request to the Fal.ai Sora-2 Pro model via its API to generate the video. The system then enters a polling loop, checking the video generation status every 60 seconds until it is COMPLETED.
  Post-Processing & Upload: Once the video is ready, the workflow performs three parallel actions:
      Fetch Video & Upload to Drive: It retrieves the generated video file and uploads it to a specified folder in Google Drive for archiving.
      Generate YouTube Title: It sends the original prompt to OpenAI's GPT-5 (or another specified model) to generate an optimized, SEO-friendly title for the YouTube video.
      Publish to YouTube: It takes the generated video file and the AI-created title and uses the Upload-Post.com service to automatically publish the video to a connected YouTube channel.
  Update & Log: Finally, the workflow updates the original Google Sheet row with the URL of the archived video in Google Drive and the newly created YouTube video URL, providing a complete audit trail.

  Set up Steps

  To configure this workflow, follow these steps:

  Prepare the Google Sheet:
      Create a Google Sheet with at least these columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL.
      In the n8n "Get new video" and update nodes, configure the documentId and sheetName to point to your specific Google Sheet.

  Configure Fal.ai API Key:
      Create an account on fal.ai and obtain your API key.
      In both the "Create Video" and "Get status" HTTP Request nodes, set up the HTTP Header Authentication.
      Set the Name to Authorization and the Value to Key YOUR_API_KEY.

  Set up Upload-Post.com for YouTube:
      Create an account on Upload-Post.com and get your API key. Connect your YouTube channel as a "profile".
      In the "HTTP Request" node (for uploading), configure the Header Auth with Name: Authorization and Value: Apikey YOUR_UPLOAD_POST_API_KEY.
      Replace YOUR_USERNAME in the node's body parameters with the profile name you created on Upload-Post.com (e.g., test1).

  Configure OpenAI (Optional but Recommended):
      The "Generate title" node uses an OpenAI model. Ensure you have valid OpenAI API credentials set up in n8n for this node to function and create optimized titles.

  Finalize Paths and Activate:
      In the "Upload Video" node, specify the correct Google Drive folder ID where you want the videos to be saved.
      Once all credentials and paths are set, you can activate the workflow and set the "Schedule Trigger" node to run at your desired interval (e.g., every 5 minutes).

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

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name: Automate Freelance Project Intake with Custom Proposals using Jotform & Gemini
author_name: iamvaar
author_username: iamvaar
categories: []
created_at: 2025-10-13T14:04:57.194Z
updated_at: 2025-10-13T14:04:57.194Z
url: https://n8n.io/workflows/9577
scraped_at: 2025-12-24 13:02:41
description:
  Workflow explaination: https://youtu.be/ecafBTFPuvE?si=7csA1yNsaUxUG72F

  This workflow is designed to automatically handle new freelance project requests from a JotForm, analyze the requirements using AI, create a custom proposal, log the details in a Google Sheet, and send a personalized response to the client.

  1. JotForm Trigger

  Purpose**: This node is the entry point of the entire automation. It waits for a new freelance project submission from your specified JotForm.
  Action: When a potential client fills out and submits the form, this node **instantly triggers the workflow, passing all submitted data (name, email, project requirements, and budget) to the next node.
  Key Detail**: Uses a webhook for real-time activation, ensuring immediate processing of every new project request.

  2. AI Agent

  Purpose**: The central brain of your freelance workflow. 🧠 It takes the project submission and turns it into a structured, customized proposal.
  Action**: The agent follows a prompt sequence to perform these tasks:

    Calls the My Freelance Document Tool: Fetches your Google Doc containing details about your services, pricing, and project templates — your “source of truth.”
    Analyzes the Project Request: Reads the client’s requirements and goals from the form.
    Generates a Custom Proposal: Based on scope, budget, and relevance to your offerings, it prepares a short, tailored proposal or quote that fits the project.
    Creates a Personalized Email: Builds an HTML email with the proposal embedded, including next steps or a scheduling link for further discussion.
    Outputs Structured Data: Packages everything (project summary, proposal text, email subject, and body) into a clean JSON object for downstream use.

  3. Append or Update Row in Sheet (Google Sheets)

  Purpose**: Serves as your lightweight CRM for all project inquiries.
  Action**: Logs data from the AI Agent (proposal details, client info, and project summary) into a Google Sheet.
  Key Detail: Configured to **Append or Update—if an email already exists, it updates that row instead of duplicating. Keeps your client records clean and organized.

  4. If

  Purpose**: Acts as a control node to decide whether a proposal email should be sent.
  Action**: Checks the output from the AI Agent to ensure the proposal text is valid (not empty).
  Key Detail**: If the proposal generation fails or returns “NAN,” the workflow stops here to avoid sending incomplete responses.

  5. Send a Message (Gmail)

  Purpose**: Sends the final personalized proposal email to the client.
  Action: Pulls the recipient’s email from the sheet and sends the **AI-generated subject and HTML proposal email automatically.
  Key Detail**: The email is customized per project, giving the client an instant, professional response with no manual effort.

nodes_used:
  ["n8n-nodes-base.jotFormTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.if","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleDocsTool","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

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name: AI based Data Analysis, Data Visualization and Data Report with Ada.im
author_name: Ada.im
author_username: ada
categories: []
created_at: 2025-10-14T07:39:50.361Z
updated_at: 2025-10-14T07:39:50.361Z
url: https://n8n.io/workflows/9605
scraped_at: 2025-12-24 13:02:41
description:
  How it works:

  This template demonstrates how to build a low-code, AI-powered data analysis workflow in n8n. It enables you to connect to various data sources (such as MySQL, Google Sheets, or local files), process and analyze structured data, and generate natural language insights and visualizations using external AI APIs.

  Key Features:

  Flexible data source selection (MySQL, Google Sheets, Excel/CSV, etc.)

  AI-driven data analysis, interpretation, and visualization via HTTP Request nodes

  Automated email delivery of analysis results (Gmail node)

  Step-by-step sticky notes for credential setup and workflow customization

  Step-by-step:
  Apply for an API Key

  You can easily create and manage your API Key in the ADA official website - API. To begin with, You need to register for an ADA account.

  Once on the homepage, click the bottom left corner to access the API management dashboard.



  Here, you can create new APIs and set the credit consumption limit for each API. A single account can create up to 10 APIs.



  After successful creation, you can copy the API Key to set credentials. You can also view the credit consumption of each API and manage your APIs.



  Set credentials

  In HTTP nodes(DataAnalysis, DataInterpretation, and DataVisualization) select Authentication → Generic Credential Type


  Choose Header Auth → Create new credential


  Name the header Authorization, which must be exactly 'Authorization', and fill in the previously applied API key


  Data Source:

  The workflow starts by extracting structured data from your chosen source (e.g., database, spreadsheet, or file).

  AI Skills:

  Data is sent to external AI APIs for analysis, interpretation, and visualization, based on your configured queries.

  Result Processing:

  The AI-generated results are converted to HTML or Markdown as needed.

  Output:

  The final report or visualization is sent via email. You can easily adapt this step to other output channels.

  API Keys Required:

  Ada API Key: For AI data analysis

  Gmail OAuth2: For sending emails (if using Gmail node)

  (Optional) Data source credentials: For MySQL, Google Sheets, etc.

nodes_used:
  ["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.mySql","n8n-nodes-base.aggregate","n8n-nodes-base.googleSheets","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.convertToFile","n8n-nodes-base.markdown","n8n-nodes-base.markdown","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.code","n8n-nodes-base.set"]

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name: Build a Knowledge Base Chatbot with Jotform, RAG Supabase, Together AI & Gemini
author_name: iamvaar
author_username: iamvaar
categories: []
created_at: 2025-10-14T12:34:58.992Z
updated_at: 2025-10-14T12:34:58.992Z
url: https://n8n.io/workflows/9626
scraped_at: 2025-12-24 13:02:41
description:
  Youtube Video: https://youtu.be/dEtV7OYuMFQ?si=fOAlZWz4aDuFFovH

  Workflow Pre-requisites

  Step 1: Supabase Setup

  First, replace the keys in the "Save the embedding in DB" & "Search Embeddings" nodes with your new Supabase keys. After that, run the following code snippets in your Supabase SQL editor:

  Create the table to store chunks and embeddings:
          CREATE TABLE public."RAG"
      (
          id bigserial PRIMARY KEY,
          chunk text NULL,
          embeddings vector(1024) NULL
      )
      TABLESPACE pg_default;
      
  Create a function to match embeddings:
          DROP FUNCTION IF EXISTS public.matchembeddings1(integer, vector);

      CREATE OR REPLACE FUNCTION public.matchembeddings1(
          match_count integer,
          query_embedding vector
      )
      RETURNS TABLE (
          chunk text,
          similarity float
      )
      LANGUAGE plpgsql
      AS $$
      BEGIN
          RETURN QUERY
          SELECT
              R.chunk,
              1 - (R.embeddings &lt;=&gt; query_embedding) AS similarity
          FROM public."RAG" AS R
          ORDER BY R.embeddings &lt;=&gt; query_embedding
          LIMIT match_count;
      END;
      $$;
  Step 2: Create Jotform with these fields
  Your full name
  email address
  Upload PDF Document [field where you upload the knowledgebase in PDF]

  Step 3: Get Together AI API Key

  Get a Together AI API key and paste it into the "Embedding Uploaded document" node and the "Embed User Message" node.

  Here is a detailed, node-by-node explanation of the n8n workflow, which is divided into two main parts.

  Part 1: Ingesting Knowledge from a PDF

  This first sequence of nodes runs when you submit a PDF through a Jotform. Its purpose is to read the document, process its content, and save it in a specialized database for the AI to use later.

  JotForm Trigger
      Type: Trigger
      What it does: This node starts the entire workflow. It's configured to listen for new submissions on a specific Jotform. When someone uploads a file and submits the form, this node activates and passes the submission data to the next step.

  Grab New knowledgebase
      Type: HTTP Request
      What it does: The initial trigger from Jotform only contains basic information. This node makes a follow-up call to the Jotform API using the submissionID to get the complete details of that submission, including the specific link to the uploaded file.

  Grab the uploaded knowledgebase file link
      Type: HTTP Request
      What it does: Using the file link obtained from the previous node, this step downloads the actual PDF file. It's set to receive the response as a file, not as text.

  Extract Text from PDF File
      Type: Extract From File
      What it does: This utility node takes the binary PDF file downloaded in the previous step and extracts all the readable text content from it. The output is a single block of plain text.

  Splitting into Chunks
      Type: Code
      What it does: This node runs a small JavaScript snippet. It takes the large block of text from the PDF and chops it into smaller, more manageable pieces, or "chunks," each of a predefined length. This is critical because AI models work more effectively with smaller, focused pieces of text.

  Embedding Uploaded document
      Type: HTTP Request
      What it does: This is a key AI step. It sends each individual text chunk to an embeddings API. A specified AI model converts the semantic meaning of the chunk into a numerical list called an embedding or vector. This vector is like a mathematical fingerprint of the text's meaning.

  Save the embedding in DB
      Type: Supabase
      What it does: This node connects to your Supabase database. For every chunk, it creates a new row in a specified table and stores two important pieces of information: the original text chunk and its corresponding numerical embedding (its "fingerprint") from the previous step.

  Part 2: Answering Questions via Chat

  This second sequence starts when a user sends a message. It uses the knowledge stored in the database to find relevant information and generate an intelligent answer.

  When chat message received
      Type: Chat Trigger
      What it does: This node starts the second part of the workflow. It listens for any incoming message from a user in a connected chat application.

  Embend User Message
      Type: HTTP Request
      What it does: This node takes the user's question and sends it to the exact same embeddings API and model used in Part 1. This converts the question's meaning into the same kind of numerical vector or "fingerprint."

  Search Embeddings
      Type: HTTP Request
      What it does: This is the "retrieval" step. It calls a custom database function in Supabase. It sends the question's embedding to this function and asks it to search the knowledge base table to find a specified number of top text chunks whose embeddings are mathematically most similar to the question's embedding.

  Aggregate
      Type: Aggregate
      What it does: The search from the previous step returns multiple separate items. This utility node simply bundles those items into a single, combined piece of data. This makes it easier to feed all the context into the final AI model at once.

  AI Agent & Google Gemini Chat Model
      Type: LangChain Agent & AI Model
      What it does: This is the "generation" step where the final answer is created.
          The AI Agent node is given a detailed set of instructions (a prompt).
          The prompt tells the Google Gemini Chat Model to act as a professional support agent.
          Crucially, it provides the AI with the user's original question and the aggregated text chunks from the Aggregate node as its only source of truth.
          It then instructs the AI to formulate an answer based only on that provided context, format it for a specific chat style, and to say "I don't know" if the answer cannot be found in the chunks. This prevents the AI from making things up.

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name: Host Your Own JWT Authentication System with Data Tables and Token Management
author_name: Luka Zivkovic
author_username: zivkovic58
categories: []
created_at: 2025-10-14T22:33:00.436Z
updated_at: 2025-10-14T22:33:00.436Z
url: https://n8n.io/workflows/9660
scraped_at: 2025-12-24 13:02:42
description:
  Description
  A production-ready authentication workflow implementing secure user registration, login, token verification, and refresh token mechanisms. Perfect for adding authentication to any application without needing a separate auth service.

  Get started with n8n now!

  What it does
  This template provides a complete authentication backend using n8n workflows and Data Tables:
  User Registration**: Creates accounts with secure password hashing (SHA-512 + unique salts)
  Login System**: Generates access tokens (15 min) and refresh tokens (7 days) using JWT
  Token Verification**: Validates access tokens for protected endpoints
  Token Refresh**: Issues new access tokens without requiring re-login
  Security Features**: HMAC-SHA256 signatures, hashed refresh tokens in database, protection against rainbow table attacks
  Why use this template
  No external services**: Everything runs in n8n - no Auth0, Firebase, or third-party dependencies
  Production-ready security**: Industry-standard JWT implementation with proper token lifecycle management
  Easy integration**: Simple REST API endpoints that work with any frontend framework
  Fully customizable**: Adjust token lifespans, add custom user fields, implement your own business logic
  Well-documented**: Extensive inline notes explain every security decision and implementation detail
  How to set up
  Prerequisites
  n8n instance (cloud or self-hosted)
  n8n Data Tables feature enabled
  Setup Steps
  Create Data Tables:
    users table: id, email, username, password_hash, refresh_token
    refresh_tokens table: id, user_id, token_hash, expires_at
  Generate Secret Keys:
    Run this command to generate a random secret:
    node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"
    Generate two different secrets for ACCESS_SECRET and REFRESH_SECRET
  Configure Secrets:
    Update the three "SET ACCESS AND REFRESH SECRET" nodes with your generated keys
    Or migrate to n8n Variables for better security (instructions in workflow notes)
  Connect Data Tables:
    Open each Data Table node
    Select your created tables from the dropdown
  Activate Workflow:
    Save and activate the workflow
    Note your webhook URLs
  API Endpoints
  Register: POST /webhook/register-user
  Request body:
  {
   "email": "user@example.com",
   "username": "username",
   "password": "password123"
  }
  Login: POST /webhook/login
  Request body:
  {
   "email": "user@example.com",
   "password": "password123"
  }
  Returns:
  {
   "accessToken": "...",
   "refreshToken": "...",
   "user": {...}
  }
  Verify Token: POST /webhook/verify-token
  Request body:
  {
   "access_token": "your_access_token"
  }
  Refresh: POST /webhook/refresh
  Request body:
  {
   "refresh_token": "your_refresh_token"
  }
  Frontend Integration Example (Vue.js/React)
  Login flow:
  const response = await fetch('https://your-n8n.app/webhook/login', {
   method: 'POST',
   headers: { 'Content-Type': 'application/json' },
   body: JSON.stringify({ email, password })
  });
  const { accessToken, refreshToken } = await response.json();
  localStorage.setItem('accessToken', accessToken);
  Make authenticated requests:
  const data = await fetch('https://your-api.com/protected', {
   headers: { 'Authorization': Bearer ${accessToken} }
  });
  Key Features
  Secure Password Storage**: Never stores plain text passwords; uses SHA-512 with unique salts
  Two-Token System**: Short-lived access tokens (security) + long-lived refresh tokens (convenience)
  Database Token Revocation**: Refresh tokens can be revoked for logout-all-devices functionality
  Duplicate Prevention**: Checks username and email availability before account creation
  Error Handling**: Generic error messages prevent information leakage
  Extensive Documentation**: 30+ sticky notes explain every security decision
  Use Cases
  SaaS applications needing user authentication
  Mobile app backends
  Internal tools requiring access control
  MVP/prototype authentication without third-party costs
  Learning JWT and auth system architecture
  Customization
  Token Lifespan**: Modify expiration times in "Create JWT Payload" nodes
  User Fields**: Add custom fields to registration and user profile
  Password Rules**: Update validation in "Validate Registration Request" node
  Token Rotation**: Implement refresh token rotation for enhanced security (notes included)
  Security Notes
  :warning: Important:
  Change the default secret keys before production use
  Use HTTPS for all webhook endpoints
  Store secrets in n8n Variables (not hardcoded)
  Regularly rotate secret keys in production
  Consider rate limiting for login endpoints
  Support & Documentation
  The workflow includes comprehensive documentation:
  Complete authentication flow overview
  Security explanations for every decision
  Troubleshooting guide
  Setup instructions
  FAQ section with common issues
  Perfect for developers who want full control over their authentication system without the complexity of managing separate auth infrastructure.

  Get Started with n8n now!

  Tags: authentication, jwt, login, security, user-management, tokens, password-hashing, api, backend

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name: Automate Lightroom Cloud to Instagram
author_name: Camille Roux
author_username: camilleroux
categories: []
created_at: 2025-10-15T09:43:52.777Z
updated_at: 2025-10-15T09:43:52.777Z
url: https://n8n.io/workflows/9692
scraped_at: 2025-12-24 13:02:45
description:
  Create a reusable “photos to post” queue from your Lightroom Cloud album—ideal for Lightroom-to-Instagram automation with n8n. It discovers new photos, stores clean metadata in a Data Table, and generates AI alt text to power on-brand captions and accessibility. Use it together with “Lightroom Image Webhook (Direct JPEG for Instagram)” and “Instagram Auto-Publisher for Lightroom Photos (AI Captions).”

  What it’s for

  Automate Lightroom to Instagram; centralize photo data for scheduled IG posting; prep AI-ready alt text and metadata for consistent, hands-free publishing.

  Parameters to set

  Lightroom Cloud credentials (client/app + API key)
  Album/collection ID to monitor in Lightroom Cloud
  Data Table name for the posting queue (e.g., Photos)
  AI settings: language/tone for alt text (concise, brand-aware)
  Image analysis URL: public endpoint of Workflow 2 (Lightroom Image Webhook)

  Works best with

  Workflow 2: Lightroom Image Webhook (Direct JPEG for Instagram)

  Workflow 3: Instagram Auto-Publisher for Lightroom Photos (AI Captions)

  Learn more & stay in the loop

  Want the full story (decisions, trade-offs, and tips) behind this Lightroom Cloud → Instagram automation?  
  👉 Read the write-up on my blog: camilleroux.com

  If you enjoy street & urban photography or you’re curious how I use these n8n workflows day-to-day:  
  👉 Follow my photo account on Instagram: @camillerouxphoto  
  👉 Follow me on other networks: links available on my site (X, Bluesky, Mastodon, Threads)

nodes_used:
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name: Lightroom Cloud to Instagram Auto Poster (AI Captions)
author_name: Camille Roux
author_username: camilleroux
categories: []
created_at: 2025-10-15T09:51:46.051Z
updated_at: 2025-10-15T09:51:46.051Z
url: https://n8n.io/workflows/9694
scraped_at: 2025-12-24 13:02:45
description:
  Automatically publish Lightroom photos to Instagram with short, human-sounding AI captions. This workflow pulls the next item from your Data Table queue, generates an on-brand caption from alt text + metadata, uploads via Instagram Graph API, and marks it posted. 
  Use it together with “Lightroom Cloud → Photos Queue (AI Alt Text)” and “Lightroom Image Webhook (Direct JPEG for Instagram).”

  What it’s for

  Hands-free Lightroom-to-Instagram posting: schedule, caption with AI, and publish consistently using the Instagram Graph API.

  Parameters to set

  Instagram Graph API access token and Instagram Business/Creator account ID
  Posting schedule (cron/interval) + max posts per run
  Data Table name & status fields (posted timestamp, IG media ID)
  Caption rules: tone, max length, hashtags policy, CTA style
  Image source URL: public endpoint of Workflow 2 (Lightroom Image Webhook)

  Works best with

  Workflow 1: Lightroom Cloud → Photos Queue (AI Alt Text)

  Workflow 2: Lightroom Image Webhook (Direct JPEG for Instagram)

  Learn more & stay in the loop

  Want the full story (decisions, trade-offs, and tips) behind this Lightroom Cloud → Instagram automation?  
  👉 Read the write-up on my blog: camilleroux.com

  If you enjoy street & urban photography or you’re curious how I use these n8n workflows day-to-day:  
  👉 Follow my photo account on Instagram: @camillerouxphoto  
  👉 Follow me on other networks: links available on my site (X, Bluesky, Mastodon, Threads)

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name: Sync NetSuite Customers to Salesforce Accounts & Contacts with Auto Upserts
author_name: Entech Solutions
author_username: entech
categories: []
created_at: 2025-10-15T10:12:36.151Z
updated_at: 2025-10-15T10:12:36.151Z
url: https://n8n.io/workflows/9695
scraped_at: 2025-12-24 13:02:44
description:
  Short Description

  Automatically exports customer records from NetSuite and syncs them into Salesforce — creating or updating Accounts and Contacts depending on whether the NetSuite record represents a company or an individual.

  Who is this for / Use case

  This template is designed for businesses and integration developers who:

  Use NetSuite as their ERP or CRM system.
  Need to automatically sync customer data (both companies and individuals) into Salesforce.
  Want a reliable, scalable solution that supports pagination and upserts.
  Prefer a ready-to-use, easily customizable workflow built on n8n.

  How it works

  Initialize pagination offset.
  Fetch customer records from NetSuite in batches via REST API.
  Split the retrieved array into individual items.
  Check record type — company or individual.
  Upsert to Salesforce:
  	For companies → creates/updates Account records.
  	For individuals → creates/updates both Account and Contact (linked to the Account).
  Merge results from both branches.
  Update pagination offset for the next batch.
  Repeat until all records are processed, then end the workflow.

  Setup / Configuration

  Import the workflow into your n8n instance.
  Set your NetSuite and Salesforce credentials.
  Ensure your Salesforce Account/Contact objects have a matching External ID field.
  (Optional) Adjust mapping fields or filters to your data needs.
  Execute manually or trigger on a schedule (e.g., daily sync).

nodes_used:
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name: Automate Support Ticket Prioritization with Jotform, Gemini AI, ClickUp Tasks
author_name: Zain Khan
author_username: zain
categories: []
created_at: 2025-10-15T21:44:04.960Z
updated_at: 2025-10-15T21:44:04.960Z
url: https://n8n.io/workflows/9736
scraped_at: 2025-12-24 13:02:45
description:
  Automated Support Prioritization and AI Task Creation

  This n8n workflow instantly captures support issues submitted via Jotform and efficiently routes them to the appropriate team and logging system based on the severity level defined by the customer. It then uses an AI Agent (Google Gemini) to transform the raw customer data into a clear, concise, and actionable task for the development team.

  Workflow Overview

  Ingestion & Logging: A new support ticket is received via Jotform and immediately logged into a Google Sheet as a central record.
  Priority Assessment & Routing: An If node checks the reported issue Severity.
      High/Medium Severity: The ticket details are instantly sent to a dedicated Slack channel for immediate team attention.
      Low Severity: The ticket details are sent via Gmail (acting as an internal email notification) to a support inbox, allowing for less immediate handling.
  AI Processing: An AI Agent summarizes the raw feedback into a clear, professional task description.
  Task Creation: The AI-generated task is automatically created in ClickUp for the development team to manage.

  Requirements

  To implement and run this automated support workflow, the following accounts and credentials are required:

  1. Service Credentials

  Jotform API Key:* For the *Jotform Trigger** to receive real-time form submissions.
  Google Sheets OAuth2/API Key:** To write data to the designated sheet.
  Slack OAuth2/API Key:** To post messages to the target Slack channel.
  Gmail OAuth2/API Key:** To send internal email notifications.
  Google Gemini API Key:* To power the *AI Agent** for task summarization.
  ClickUp API Key:** To create tasks in the target workspace.
  Sign up for n8n using: https://n8n.partnerlinks.io/pe6gzwqi3rqw

  2. External Configurations

  Jotform Setup:* A form configured with fields for Name, Email, Issue, Description, and the crucial *Severity** field.
  Sign up for Jotform using: https://www.jotform.com/?partner=zainurrehman
  ClickUp Setup:* The specific *Team, Space, Folder, and List IDs* must be configured in the *Create a task** node to ensure tickets are created in the correct project board.

nodes_used:
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name: Transcribe Youtube Videos for Free with youtube-transcript.io & save to Supabase
author_name: automedia
author_username: automate-social-media
categories: []
created_at: 2025-10-16T04:18:06.996Z
updated_at: 2025-10-16T04:18:06.996Z
url: https://n8n.io/workflows/9747
scraped_at: 2025-12-24 13:02:41
description:
  Transcribe New YouTube Videos and Save to Supabase

  Who's It For?

  This workflow is for content creators, marketers, researchers, and anyone who needs to quickly get text transcripts from YouTube videos. If you analyze video content, repurpose it for blogs or social media, or want to make videos searchable, this template will save you hours of manual work.

  What It Does

  This template automatically monitors multiple YouTube channels for new videos. When a new video is published, it extracts the video ID, retrieves the full transcript using the youtube-transcript.io API, and saves the structured data—including the title, author, URL, and full transcript—into a Supabase table.

  It intelligently filters out YouTube Shorts by default and includes error handling to ensure that only successful transcriptions are processed.

  Requirements

  A Supabase account with a table ready to receive the video data.
  An API key from youtube-transcript.io (offers a free tier).
  The Channel ID for each YouTube channel you want to track. You can find this using a free online tool like TunePocket's Channel ID Finder.

  How to Set Up

  Add Channel IDs:
      In the "Channels To Track" node, replace the example YouTube Channel IDs with your own. The workflow uses these IDs to create RSS links and find new videos.
  Configure API Credentials:
      Find the "youtube-captions" HTTP Request node.
      In the credentials tab, create a new "Header Auth" credential. Name it youtube-transcript-io and paste your API key into the "Value" field. The "Name" field should be x-api-key.
  Connect Your Supabase Account:
      Navigate to the "Add to Content Queue Table" node.
      Create new credentials for your Supabase account using your Project URL and API key.
      Once connected, select your target table and map the incoming fields (title, source_url, content_snippet, etc.) to the correct columns in your table.
  Set Your Schedule (Optional):
      The workflow starts with a manual trigger. To run it automatically, replace the "When clicking ‘Execute workflow’" node with a Schedule node and set your desired interval (e.g., once a day).
  Activate the Workflow:
      Save your changes and toggle the workflow to Active in the top right corner.

  How to Customize

  Transcribe YouTube Shorts:* To include Shorts in your workflow, select the *"Does url exist?"** If node and delete the second condition that checks for youtube.com/shorts.
  Change Your Database:* Don't use Supabase? Simply replace the *"Add to Content Queue Table"* node with another database or spreadsheet node, such as *Google Sheets, **Airtable, or n8n's own Table.

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name: Fast-track CV screening with AI analysis from Gmail to Slack and Google Sheets
author_name: Dean Pike
author_username: deanjp
categories: []
created_at: 2025-10-16T07:27:17.590Z
updated_at: 2025-10-16T07:27:17.590Z
url: https://n8n.io/workflows/9764
scraped_at: 2025-12-24 13:02:41
description:
  CV → Match → Screen → Decide, all automated

    This workflow automatically processes candidate CVs from email, intelligently matches them to job descriptions, performs
    AI-powered screening analysis, and sends actionable summaries to your team in Slack.

  Good to know
    Handles both PDF and Word document CVs automatically
    Two-stage JD matching: prioritizes role mentioned in candidate's email, falls back to CV analysis if needed
    Uses Google Gemini API for AI screening (generous free tier and rate limits, typically enough to avoid paying for API requests, but check latest pricing at Google AI Pricing)
    All CVs stored in Google Drive with standardized naming (candidate name + date/time)
    Complete audit trail logged in Google Sheets

  Who's it for
    Hiring teams and recruiters who want to automate first-round CV screening while maintaining quality. Perfect for companies        
    receiving high volumes of applications across multiple roles, especially in tech, sales, or automation-focused positions.

  How it works
    Gmail monitors inbox for CVs with specific label and downloads attachments
    Detects file type (PDF or Word) and converts/standardizes format for text extraction
    AI agent matches candidate to best-fit job description by analyzing email context first (if candidate mentioned a role), or    
     CV content as fallback (selects up to 3 potential JD matches)
    If multiple JDs matched, second AI agent selects the single best fit
    AI recruiter agent analyzes CV against selected JD and generates structured screening report (strengths, weaknesses,
    risk/reward factors, overall fit score 0-10 with justification)
    Extracts candidate details (name, email) from CV text
    Logs complete analysis to Google Sheets tracker
    Sends formatted summary to Slack with Proceed/Reject action buttons for instant team decisions

  Requirements
    Gmail account with API access
    Google Drive account (OAuth2)
    Google Sheets account (OAuth2)
    Slack workspace with bot permissions
    Google Gemini API key (Get free key here)
    Google Drive folders: one for CVs, one for Job Descriptions (as PDFs or Google Docs)

  How to set up
    Add credentials: Gmail OAuth2, Google Drive OAuth2, Google Sheets OAuth2, Slack OAuth2, Google Gemini API
    Create Gmail label (e.g., "CV-Screening") for incoming candidate emails
    In "Receive CV via Email" node: select your Gmail label for filtering
    Create two Google Drive folders: "Candidate CVs" and "Job Descriptions"
    In "Upload CV - PDF" and "Stream Doc/Docx File" nodes: update folder ID to your "Candidate CVs" folder
    In "Access JD Files" node: update folder ID to your "Job Descriptions" folder
    Create Google Sheet named "AI Candidate Screening" with columns matching the sample AI Candidate Screening sheet       
    In "Append row in sheet" node: select your Google Sheet
    In "Send Candidate Screening Confirmation" node: select your Slack channel
    Activate workflow

  Customizing this workflow
    Change JD matching logic: Edit "JD Matching Agent" node prompt to adjust how CVs are matched to roles (e.g., weight
    technical skills vs. experience).
    Change "Company Description" in AI prompts: Insert your "Company Description" in System Message sections in "JD Matching Agent" and "Detailed JD Matching Agent" nodes
    Modify screening criteria: Edit "Recruiter Scoring Agent" node system message to focus on specific qualities (culture       
    fit, leadership, technical depth, etc.)
    Add more storage locations: Add nodes to save CVs to other systems (Notion, Airtable, ATS platforms)
    Customize Slack message: Edit "Send Candidate Screening Confirmation" node to change formatting, add more context, or       
    include additional candidate data
    Auto-proceed logic: Add IF node after screening to auto-proceed candidates with fit score above threshold (e.g., 8+/10)     
    Add email responses: Connect nodes to automatically email candidates (confirmation, rejection, interview invite)
    Add human-in-the-loop: Sub-workflow triggered by Slack response or email response, to update Sheet with approve/reject status
  Add candidate email responses + interview scheduling**: For approved candidates, trigger email to candidate with Cal.com or Calendly link so they can book their interview

  Quick Troubleshooting
    No CVs being processed: Check Gmail label is correctly set in "Receive CV via Email" node and emails are being labeled      
    Word documents failing: Verify "Stream Doc/Docx File" node has correct parent folder ID and Google Drive credentials        
    authorized
    JD matching returns no results: Check "Access JD Files" node folder ID points to your Job Descriptions folder, and JD       
    files are named clearly (e.g., "Marketing Director JD.pdf")
   JD matching is not relevant for my company: Update the "Company Description" in the System Messages in the "JD Matching Agent" and "Detailed JD Matching Agent" nodes
    "Can't find matching JD": Ensure candidate's email mentions role name OR their CV clearly indicates relevant experience     
    for available JDs
    Google Sheets errors: Verify sheet name is "AI Candidate Screening" and column headers exactly match workflow
    expectations (Submission ID, Date, CV, First Name, etc.)
    Slack message not appearing: Re-authorize Slack credentials and confirm channel ID in "Send Candidate Screening
    Confirmation" node
    Missing candidate name/email: CV text must be readable - check PDF extraction quality or try converting complex CVs to      
    simpler format
    401/403 API errors: Re-authorize all OAuth2 credentials (Gmail, Google Drive, Google Sheets, Slack)
    AI analysis quality issues: Edit system prompts in "JD Matching Agent" and "Recruiter Scoring Agent" nodes to refine        
    screening criteria
  Sample Outputs
  Google Sheets - AI Candidate Screening - sample


  Slack confirmation message

  Acknowledgments
    This workflow was inspired by Nate Herk's YouTube demonstration on building a resume analysis system. This implementation builds upon that foundation by adding dynamic job description matching (initial + detailed JD matching agents), Slack Block Kit integration with interactive buttons, updated Google Drive API methods for document handling, and enhanced candidate data capture in Google Sheets.

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name: Cross-Post Tiktok Videos to Multiple Social Media Platforms with RSS & Blotato
author_name: Sabrina Ramonov 🍄
author_username: sabrina-ramonov
categories: []
created_at: 2025-10-16T13:29:07.736Z
updated_at: 2025-10-16T13:29:07.736Z
url: https://n8n.io/workflows/9780
scraped_at: 2025-12-24 13:02:41
description:
  Description
  This automation detects when you post a Tiktok video, automatically downloads the video without watermark, stores it in Google Drive, and reposts your Tiktok video to other social media platforms. All on autopilot. So you can grow your presence on multiple platforms, without more work. You can also easily add steps to customize captions per platform.

  Youtube Tutorial
  https://www.youtube.com/watch?v=yHbyEb-fBGY

  📄 Documentation
  Full Step-by-Step Documentation

  How It Works

  1. Trigger
  RSS feed triggers when you post a new Tiktok video

  2. Fetch Video
  Download the newly posted Tiktok video (without watermark)  
  Store video in Google Drive

  3. Publish to Social Media
  Connect Blotato to your social accounts  
  Choose your social accounts  
  Post immediately or schedule for later  

  Setup & Required Accounts
  Enable "Verified Community Nodes" in your n8n Admin Panel  
  Install "Blotato" verified community node  
  Sign up for Blotato: create API key at Dashboard → API Keys, then create your Blotato credential and connect your social accounts
  Sign up for RSS.app: create feed from your TikTok profile, copy RSS URL into the RSS Feed Trigger node, and set "Number of Posts" to 1  
  Google Drive account to store downloaded Tiktok videos

  Tips & Tricks
  Ensure your RSS feed outputs only 1 item at a time  
  For multiple posts within an hour, set RSS.app refresh to 15 minutes (paid plan)  
  While testing: enable only 1 social platform, deactivate others, and consider scheduling posts in the future  
  After the workflow finishes, check your social account for the final post; if successful, enable another social media node and continue testing

  Troubleshooting
  Check your Blotato API Dashboard to see every request, response, and error. Click on a request to see the details.

  Need Help?
  In the Blotato web app, click the orange button on the bottom right corner. This opens the Support messenger where I help answer technical questions.

  Connect with me: Linkedin | Youtube

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name: AI-Powered Customer Feedback Analysis & Routing for Gmail, Zendesk, Slack & Pipedrive
author_name: PollupAI
author_username: Pollup
categories: []
created_at: 2025-10-16T13:51:11.955Z
updated_at: 2025-10-16T13:51:11.955Z
url: https://n8n.io/workflows/9782
scraped_at: 2025-12-24 13:02:46
description:
  Who's it for
  This workflow is for Customer Success, Product, and Support teams who need to centralize and analyze unstructured customer feedback. It automates the process of identifying key themes from various communication channels, allowing you to proactively address issues, track feature requests, and understand the voice of the customer without manual effort.

  What it does
  This workflow uses a powerful chain of AI agents to process customer feedback from end to end. It begins by using a Data Agent to gather all recent customer interactions from multiple sources, including Gmail, Pipedrive, Zendesk, and Slack.

  Once the raw data is collected, a second AI Chain reads all the text and compresses it into concise, actionable "signals." A third AI Chain then takes these signals and intelligently clusters them into shared topics, assigning each a human-readable label like "Billing," "Performance," or "Feature Request."

  Finally, a fourth AI Agent acts as a dispatcher. It analyzes the clustered topics and follows a set of routing rules defined in its prompt to take the appropriate action. It uses its tools to automatically create a Zendesk ticket for product feedback, send a Slack message for billing issues, create a Notion page for training opportunities, or send a direct email alert for high-risk accounts.

  How to set up
  To get this workflow running, you will need to configure the credentials and parameters for the following nodes:
  Configure Credentials: Add your credentials for the Config: Set LLM for Agents node and all of the Tool nodes (Gmail, Pipedrive, Zendesk, Slack, and Notion).
  Set Initial Parameters: In the Set: Initial Parameters node, update the placeholder email address and the Slack channel name for billing alerts.
  Update Slack Search Channel: In the Tool: Search Slack Messages node, set the channel you want the agent to search for feedback in.
  Activate Workflow: Once configured, you can run the workflow manually to start the analysis.

  Requirements
  An account with an LLM provider, such as OpenAI.
  Accounts for the services you wish to connect (Gmail, Pipedrive, Zendesk, Slack, Notion).
  This workflow requires n8n's Langchain community nodes to be installed on your instance.

  How to customize the workflow
  This workflow's logic is primarily driven by AI prompts, making it highly customizable:
  AI Prompts:** Adjust the prompts in any of the AI Agent or AI Chain nodes to change the data gathering, analysis, clustering, or routing rules to fit your business needs.
  Data Sources:** Add, remove, or swap out the "Tool" nodes in the AI Agent: Gather Customer Feedback section to connect to different data sources like Intercom, Salesforce, or a database.
  Triggers:** Replace the Manual Trigger with a Schedule Trigger to run the analysis automatically on a daily or weekly basis.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.gmailTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.zendeskTool","n8n-nodes-base.slackTool","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.zendeskTool","n8n-nodes-base.gmailTool","n8n-nodes-base.notionTool","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, 6644 characters]


name: Automated Structured Data Extract & Summary via Decodo + Gemini & Google Sheets
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-10-16T15:43:47.813Z
updated_at: 2025-10-16T15:43:47.813Z
url: https://n8n.io/workflows/9789
scraped_at: 2025-12-24 13:02:46
description:
  Who this is for

  This workflow is designed for:

  Automation engineers building AI-powered data pipelines

  Product managers & analysts needing structured insights from web pages

  Researchers & content teams extracting summaries from documentation or articles

  HR, compliance, and knowledge teams converting unstructured web content into structured records

  n8n self-hosted users leveraging advanced scraping and LLM enrichment

  It is ideal for anyone who wants to transform any public URL into structured data + clean summaries automatically.

  What problem this workflow solves

  Web content is often unstructured, verbose, and inconsistent, making it difficult to:

  Extract structured fields reliably

  Generate consistent summaries

  Reuse data across spreadsheets, dashboards, or databases

  Eliminate manual copy-paste and interpretation

  This workflow solves the problem of turning arbitrary web pages into machine-readable JSON and human-readable summaries, without custom scrapers or manual parsing logic.

  What this workflow does

  The workflow integrates Decodo, Google Gemini, and Google Sheets to perform automated extraction of structured data.

  Here’s how it works step-by-step:

  Input Setup

     The workflow begins when the user executes it manually or passes a valid URL.
     The input includes url.

  Profile Extraction with Decodo

  Accepts any valid URL as input

  Scrapes the page content using Decodo

  Uses Google Gemini to:

  Extract structured data in JSON format

  Generate a concise, factual summary

  Cleans and parses AI-generated JSON safely

  Merges structured data and summary output

  Stores the final result in Google Sheets for reporting or downstream automation

  JSON Parsing & Merging

     The Code Node cleans and parses the JSON output from the AI for reliable downstream use.
     The Merge Node combines both structured data and the AI-generated summary.

  Data Storage in Google Sheets

     The Google Sheets Node appends or updates the record, storing the structured JSON and summary into a connected spreadsheet.

  End Output

     A unified, machine-readable data in JSON + an executive-level summary suitable data analysis or downstream automation.

  Setup Instructions

  Prerequisites

  n8n account** with workflow editor access
  Decodo API credentials** - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard 





  Google Gemini (PaLM) API access**
  Google Sheets OAuth credentials**

  Setup Steps

  Import the workflow into your n8n instance.
  Configure Credentials

     Add your Decodo API credentials in the Decodo node.
     Connect your Google Gemini (PaLM) credentials for both AI nodes.
     Authenticate your Google Sheets account.
  Edit Input Node

     In the Set the Input Fields node, replace the default URL with your desired profile or dynamic data source.
  Run the Workflow

     Trigger manually or via webhook integration for automation.
     Verify that structured profile data and summary are written to the linked Google Sheet.

  How to customize this workflow to your needs

  You can easily extend or adapt this workflow:

  Modify Structured Output

  Change the Gemini extraction prompt to match your own JSON schema
  Add required fields such as authors, dates, entities, or metadata

  Improve Summarization

  Adjust summary length or tone (technical, executive, simplified)
  Add multi-language summarization using Gemini

  Change Output Destination

  Replace Google Sheets with:

    Databases (Postgres, MySQL)
    Notion
    Slack / Email
    File storage (JSON, CSV)

  Add Validation or Filtering

  Insert IF nodes to:

    Reject incomplete data
    Detect errors or hallucinated output
    Trigger alerts for malformed JSON

  Scale the Workflow

  Replace manual trigger with:

    Webhook
    Scheduled trigger
    Batch URL processing

  Summary

  This workflow provides a powerful, generic solution for converting unstructured web pages into structured, AI-enriched datasets.

  By combining Decodo for scraping, Google Gemini for intelligence, and Google Sheets for persistence, it enables repeatable, scalable, and production-ready data extraction without custom scrapers or brittle parsing logic.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","@decodo/n8n-nodes-decodo.decodo","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.merge","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini"]

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name: Safely Update n8n with Version Checks and Telegram Notifications
author_name: David Hernández Luján
author_username: davidhluj
categories: []
created_at: 2025-10-16T18:14:47.609Z
updated_at: 2025-10-16T18:14:47.609Z
url: https://n8n.io/workflows/9792
scraped_at: 2025-12-24 13:02:46
description:
  Who’s it for
  This workflow is for system administrators or self-hosted n8n users who want to automatically check and update their n8n instance to the latest version — with Telegram notifications for every step.

  How it works
  The workflow runs daily at 9 AM or every time n8n starts.
  It retrieves your current version using the Execute Command node.
  It checks the latest release from the official n8n GitHub API.
  It compares both versions and decides whether an update is needed.
  If an update is available:
     Sends a Telegram alert.
     Verifies that there are no running executions.
     Runs the update command safely.
     Sends a confirmation message when done.
  If your instance is already up to date, it sends a “latest version” message instead.

  Requirements
  Self-hosted n8n** instance with access to run terminal commands.
  A valid Telegram Bot API credential (configured in n8n Credentials; not hardcoded).
  SSH credentials**
  To run commands on the server where n8n is installed
  n8n API credentials**
  To query running executions

  How to set up
  Import this workflow into your n8n instance.
  Connect your Telegram Bot credential to the Telegram nodes.
  Adjust the chat ID and message thread ID if needed.
  (Optional) Change the schedule time in the Schedule Trigger node.
  Save and activate the workflow.

  How to customize
  Change the update command if you’re running n8n via Docker:
      docker pull n8nio/n8n:latest

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.function","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.if","n8n-nodes-base.n8n","n8n-nodes-base.n8nTrigger","n8n-nodes-base.wait","n8n-nodes-base.ssh","n8n-nodes-base.ssh"]

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name: Summarize Meeting Transcripts with GPT-4 & Sentiment Analysis for Gmail
author_name: Dhinesh Ravikumar
author_username: dk10rk
categories: []
created_at: 2025-10-16T21:30:37.291Z
updated_at: 2025-10-16T21:30:37.291Z
url: https://n8n.io/workflows/9801
scraped_at: 2025-12-24 13:02:41
description:
  Who it's for
  Project managers, AI builders, and teams who want structured, automated meeting summaries with zero manual work.

  What it does
  This workflow monitors a Google Drive folder for new meeting notes (PDF/TXT), extracts text, summarizes it via OpenAI GPT-4o, groups tasks by sentiment, builds a styled HTML summary, and sends it via Gmail.

  How to set it up
  Connect Google Drive, OpenAI, and Gmail credentials.  
  Point the Drive Trigger to your meeting notes folder.  
  Paste the system prompt into the AI node.  
  Set Gmail Email Type to HTML and Message to {{$json.email_html}}.  
  Drop a test file and execute once.

  Requirements
  n8n account  
  Google Drive, OpenAI, and Gmail credentials  
  Non-scanned PDFs or plain text files

  Customization ideas
  Add Slack or Notion logging  
  Support additional file types  
  Translate summaries automatically

  Tags
  #ai #automation #productivity #gmail #drive #meeting-summary #openai

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.extractFromFile","n8n-nodes-base.if","n8n-nodes-base.extractFromFile","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","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-nodes-base.code","n8n-nodes-base.code"]

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name: Personalized Email Outreach with LinkedIn & Crunchbase Data and Gemini AI Review
author_name: Johnny Rafael
author_username: johnnyrafael
categories: []
created_at: 2025-10-17T07:22:21.599Z
updated_at: 2025-10-17T07:22:21.599Z
url: https://n8n.io/workflows/9814
scraped_at: 2025-12-24 13:02:41
description:
  AI-Enriched Cold Outreach: Research → Draft → QA → Write-back


  What this template does
  Automates cold email drafting from a lead list by:
  Enriching each lead with LinkedIn profile, LinkedIn company, and Crunchbase data  
  Generating a personalized subject + body with Gemini  
  Auto-reviewing with a Judge agent and writing back only APPROVED drafts to your Data Table  

  Highlights
  Hands-off enrichment via RapidAPI; raw JSON stored back on each row  
  Two-agent pattern: Creative Outreach Agent (draft) + Outreach Email Judge (QA)  
  Structured outputs guaranteed by LangChain Structured Output Parsers  
  Data Table–native: reads “unprocessed” rows, writes results to the same row  
  Async polling with Wait nodes for scraper task results  

  How it works (flow)
  Trigger: Manual (replace with Cron if needed)  
  Fetch leads: Data Table “Get row(s)” filters rows where email_subject is empty (pending)  
  Loop: Split in Batches iterates rows  
  Enrichment (runs in parallel):
     LinkedIn profile: HTTP (company_url) → Wait → Results → Data Table update → linkedin_profile_scrape  
     LinkedIn company: HTTP (company_url) → Wait → Results → Data Table update → linkedin_company_scrape  
     Crunchbase company: HTTP (url_search) → Wait → Results → Data Table update → crunchbase_company_scrape  
     (All calls use host cold-outreach-enrichment-scraper with a RapidAPI key.)  
  Draft (Gemini): “Agent One” composes a concise, personalized email using row fields + enrichment + ABOUT ME block.  
     Structured Output Parser enforces:  
            {
         "email_subject": "text",
         "email_content": "text"
       }
       Prep for QA: “Email Context” maps email_subject, email_content, and email for the judge.  
  QA (Judge): “Judge Agent” returns APPROVED or REVISE (brief feedback allowed).  
  Route:
     If APPROVED → Data Table “Update row(s)” writes email_subject + email_body (a.k.a. email_content) back to the row.  
     If REVISE → Skipped; loop continues.  

  Required setup
  Data Table: “email_linkedin_list” (or your own) with at least:  
  email, First_name, Last_name, Title, Location, Company_Name, Company_site,  
    Linkedin_URL, company_linkedin (if used), Crunchbase_URL,  
    email_subject, email_body,  
    linkedin_profile_scrape, linkedin_company_scrape, crunchbase_company_scrape (string fields for JSON).  

  Credentials:  
  RapidAPI key for cold-outreach-enrichment-scraper (store securely as credential, not hardcoded)  
  Google Gemini (PaLM) API configured in the Google Gemini Chat Model node  

  ABOUT ME block:  
  Replace the sample persona (James / CEO / Company Sample / AI Automations) with your own.

  Nodes used
  Data Table**
  HTTP Request:**  
  AI Agent:**
  Google Gemini Chat Model**  
  Split in Batches:** Main Loop  
  Set:** RapidAPI-Key

  Customization ideas
  Process flags:** Add email_generated_at or processed boolean to prevent reprocessing.  
  Human-in-the-loop:** Send drafts to Slack/Email for spot check before write-back.  
  Delivery:** After approval, optionally email the draft to the sender for review.  

  Quotas & costs
  RapidAPI: Multiple calls per row (three tasks + result polls).  
  Gemini: Token usage for generator + judge per row.  
  Tune batch size and schedule accordingly.  

  Privacy & compliance
  You are scraping and storing person/company data.  
  Ensure lawful basis, respect ToS, and minimize stored data.  

nodes_used:
  ["@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.manualTrigger","n8n-nodes-base.dataTable","n8n-nodes-base.dataTable","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.dataTable","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.dataTable","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.dataTable","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.dataTable","n8n-nodes-base.httpRequest","n8n-nodes-base.executeWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8612 characters]


name: Track Crypto Market Gainers & Losers with CoinGecko and Discord Bot
author_name: Malik Hashir
author_username: malikx
categories: []
created_at: 2025-10-17T20:38:39.379Z
updated_at: 2025-10-17T20:38:39.379Z
url: https://n8n.io/workflows/9854
scraped_at: 2025-12-24 13:02:46
description:
  Purpose
  Automate cryptocurrency market monitoring by tracking top 24-hour gainers and losers from 1750+ coins, delivering professional Discord (optional Telegram, Slack etc) updates with rich embeds and real-time data.

  How It Works
  This intelligent workflow fetches comprehensive cryptocurrency data from CoinGecko's API across multiple pages, processes thousands of coins to identify the most significant market movers, and automatically posts formatted updates to your Discord server. The system filters, ranks, and presents data in an easily digestible format with detailed coin information, price metrics, and visual indicators.

  Who Is It For
  Crypto Community Managers running Discord servers
  Trading Groups & Investment Communities
  Crypto Influencers & Content Creators
  DeFi Projects & DAOs monitoring market trends
  Crypto Enthusiasts wanting automated market insights

  Setup Overview
  Obtain API keys from CoinGecko
  Configure Discord bot credentials with proper permissions
  Set your server and channel IDs
  Import the workflow and connect the nodes
  Test and schedule automatic execution

  Value Proposition
  💰 Cost Savings: Eliminate manual market monitoring - save 5-10 hours weekly
  ⏰ Time Efficiency: Automated data collection and reporting
  🚀 Community Engagement: Keep your community informed with timely updates
  📈 Market Awareness: Stay ahead of market trends without constant manual checking
  🔧 Scalable Solution: Handles 1750+ coins effortlessly, easily expandable

  Perfect for: Crypto communities, trading groups, market analysts, and anyone needing automated cryptocurrency market intelligence delivered directly to Discord with professional formatting and real-time insights.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.limit","n8n-nodes-base.limit","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.discord","n8n-nodes-base.discord","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.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Transform Long Videos into Viral Shorts with AI and Schedule to Social Media using Whisper & Gemini
author_name: Juan Carlos Cavero Gracia
author_username: carlosgracia
categories: []
created_at: 2025-10-18T17:27:07.808Z
updated_at: 2025-10-18T17:27:07.808Z
url: https://n8n.io/workflows/9867
scraped_at: 2025-12-24 13:02:41
description:
  This automation template turns any long video into multiple viral-ready short clips and auto-schedules them to TikTok, Instagram Reels, and YouTube Shorts. It works with both vertical and horizontal inputs and respects the original input resolution (no unnecessary upscaling), cropping or letterboxing intelligently when needed. The workflow automatically extracts between 3 and 6 clips (based on video length and the most engaging segments) and schedules one short per consecutive day—e.g., 3 clips → the next 3 days, 6 clips → the next 6 days.

  Note: This workflow uses OpenAI Whisper for word-level transcription, Google’s Gemini for clip selection and metadata, and Upload-Post’s FFmpeg API for GPU-accelerated cutting/cropping and social scheduling. You can use the same Upload-Post API token for both FFmpeg jobs and publishing uploads. Upload-Post also offers a generous free trial with no credit card required.*

  Who Is This For?
  Creators & Editors:** Batch-convert long talks/podcasts into daily Shorts/Reels/TikToks.
  Agencies & Social Teams:** Turn webinars/interviews into a reliable short-form stream.
  Brands & Founders:** Maintain a steady posting cadence with minimal hands-on editing.

  What Problem Does This Workflow Solve?
  Manual clipping is slow and inconsistent. This workflow:
  Finds Hooks Automatically:** AI picks 3–6 high-retention segments from transcript + timestamps (count scales with video length/quality).
  Cuts Cleanly:** Absolute-second FFmpeg timing to avoid mid-word cuts.
  Vertical & Horizontal Friendly:** Handles both orientations and respects source resolution.
  Schedules for You:** Posts one clip per day on consecutive days.

  How It Works
  Form Upload: Submit your long video.
  Audio Extraction: FFmpeg job extracts audio for accurate ASR.
  Whisper Transcription: Word-level timestamps enable precise clipping.
  AI Clip Mining (Gemini): Detects 3–6 “viral” moments (15–60s) and generates titles/descriptions.
  Cut & Crop (FFmpeg): GPU pipeline produces clean clips; preserves input resolution/orientation when possible and crops/pads appropriately for target platforms.
  Status & Download: Polls job status and retrieves the final clips.
  Auto-Scheduling (Consecutive Days): Schedules one short per day starting tomorrow, for as many days as clips were produced (e.g., 3 clips → 3 days, 6 clips → 6 days) at a configurable time (default 20:00 Europe/Madrid).

  Setup
  OpenAI (Whisper): Add your OpenAI API credentials.
  Google Gemini: Add Gemini credentials used by the AI Agent node.
  Upload-Post (free trial no credit card required): Generate your api token https://app.upload-post.com/ connect your social media accounts and add your API token credentials in n8n (same token works for FFmpeg jobs and publishing).
  Scheduling: Adjust posting time/intervals and timezone (Europe/Madrid by default).
  Metadata Mapping: Titles/descriptions are auto-generated per platform; tweak as needed.

  Requirements
  Accounts:** n8n, OpenAI, Google (Gemini), Upload-Post, and social platform connections.
  API Keys:** OpenAI token, Gemini credentials, Upload-Post token.
  Budget:** Whisper + Gemini inference + FFmpeg compute + optional posting costs.

  Features
  Word-Accurate Cuts:** Absolute-second timecodes with subtle pre/post-roll.
  Orientation-Aware:** Supports vertical and horizontal inputs; preserves source resolution where possible.
  Platform-Optimized Output:** 9:16-ready delivery with smart crop/pad behavior.
  Consecutive-Day Scheduler:** 3–6 clips → 3–6 consecutive posting days, automatically.
  Retry & Polling:** Built-in waits and status checks for robust processing.
  Modular:** Swap models, adjust clip count/length, or add/remove platforms quickly.

  Turn long-form video into a consistent sequence of Shorts/Reels/TikToks—automatically, day after day, while respecting your source resolution.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-upload-post.uploadPost","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.formTrigger","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","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, 8860 characters]


name: Resume Intelligence and Data Mining using Decodo with GPT-4o-mini
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-10-19T03:37:20.824Z
updated_at: 2025-10-19T03:37:20.824Z
url: https://n8n.io/workflows/9878
scraped_at: 2025-12-24 13:02:44
description:
  1. Who this is for

  This workflow is specifically designed for

  Recruiters, HR analytics teams, and data-driven talent acquisition professionals seeking deeper insights from candidate resume.
  Valuable for HR tech developers, ATS/CRM engineers, and AI-driven recruitment platforms aiming to automate candidate research.
  Helps organizations build predictive hiring models and gain actionable talent intelligence.

  2. What problem this workflow solves

  Recruiters often face information overload when analyzing candidate resume manually reviewing experiences, skills, and cultural fit is slow and inconsistent.

  Traditional scraping tools extract raw data but fail to produce actionable intelligence like career trajectory, skills alignment, and fit for a role.

  This workflow solves that by:

  Automating candidate resume data extraction through Decodo
  Structuring it into JSON Resume Schema
  Running deep AI-driven analytics using OpenAI GPT-4o-mini
  Delivering comprehensive candidate intelligence ready for ATS/CRM integration or HR dashboards

  3. What this workflow does

  This n8n workflow combines Decodo’s web scraping with OpenAI GPT-4o-mini to produce advanced recruitment intelligence.

  Flow Breakdown:

  Manual Trigger – Start the workflow manually or schedule it in n8n.
  Set Input Fields – Define resume URL, location, and job description.
  Decodo Node – Scrapes the candidate’s profile (experience, skills, education, achievements, etc.).
  Structured Data Extractor (GPT-4o-mini) – Converts the scraped data into a structured JSON Resume Schema.
  Advanced Data Mining Engine (GPT-4o-mini) 

  – Performs:

     Skills Analysis (strengths, gaps, transferable skills)
     Experience Intelligence (career trajectory, leadership, project complexity)
     Cultural Fit Insights (work style, communication style, agility indicators)
     Career Trajectory Forecasting (promotion trends, growth velocity)
     Competitive Advantage Analysis (market positioning, salary expectations)
  Summarizer Node – Produces an abstractive and comprehensive AI summary of the candidate profile.
  Google Sheets Node – Saves the structured insights automatically into your recruitment intelligence sheet.
  File Writer Node (Optional) – Writes the JSON report locally for offline storage or integration.

  The result is a data-enriched candidate intelligence report far beyond what traditional resume parsing provides.

  4. Setup

  Prerequisites

  n8n account with workflow editor access
  Decodo API credentials
  OpenAI API key
  Google Sheets account connected via OAuth2

  Make sure to install the Decodo Community node.

  Setup Steps

  Import the workflow JSON into your n8n workspace.
  Set credentials for:

     Decodo Credentials account
     OpenAI API (GPT-4o-mini)
     Google Sheets OAuth2
  In the “Set the Input Fields” node, update:

     url → Resume link
     geo → Candidate region or country
     jobDescription → Target job description for matching
  Ensure the Google Sheet ID and tab name are correct in the “Append or update row in sheet” node.
  Click Execute Workflow to start.

  5. How to customize this workflow

  You can adapt this workflow for different recruitment or analytics scenarios:

  Add Sentiment Analysis

  Add another LLM node to perform sentiment analysis on candidate recommendations or feedback notes.

  Enrich with Job Board Data

  Use additional Decodo nodes or APIs (Indeed, Glassdoor, etc.) to compare candidate profiles to live job postings.

  Add Predictive Fit Scoring

  Insert a Function Node to compute a numerical "fit score" by comparing skill vectors and job requirements.

  Automate Candidate Reporting

  Connect to Gmail, Slack, or Notion nodes to automatically send summaries or reports to hiring managers.

  6. Summary

  The Advanced Resume Intelligence & Data Mining via Decodo + OpenAI GPT-4o-mini workflow transforms traditional candidate sourcing into AI-driven intelligence gathering.

  It integrates:

  Decodo** → To perform webscraping of data
  GPT-4o-mini** → to interpret, analyze, and summarize with context
  Google Sheets** → to store structured results for real-time analysis

  With this system, recruiters and HR analysts can move from data collection to decision intelligence, unlocking faster and smarter talent insights.

nodes_used:
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workflow_json_compressed:
  [encoded data, 5892 characters]


name: Auto-Send WooCommerce Invoices via WhatsApp with Rapiwa API
author_name: Rapiwa
author_username: rapiwa
categories: []
created_at: 2025-10-19T04:53:59.196Z
updated_at: 2025-10-19T04:53:59.196Z
url: https://n8n.io/workflows/9879
scraped_at: 2025-12-24 13:02:43
description:
  Who is this for?
  This workflow listens for new or updated WooCommerce orders, cleans and structures the order data, processes orders in batches, and standardizes WhatsApp phone numbers. It verifies phone numbers via the Rapiwa API, sends invoice links or messages to verified numbers, and logs results into separate Google Sheets tabs for verified and unverified numbers. Throttling and looping are managed using batch processing and wait delays.

  What this Workflow Does
  Receives order events (e.g., order.updated) from WooCommerce or a similar trigger.
  Extracts customer, billing/shipping address, product list, and invoice link from the order payload.
  Processes orders/items in batches for controlled throughput.
  Cleans and normalizes phone numbers by removing non-digit characters.
  Verifies whether a phone number is registered on WhatsApp using the Rapiwa API.
  If verified, sends a personalized message or invoice link via Rapiwa's send-message endpoint.
  If not verified, logs the customer as unverified in Google Sheets.
  Logs every send attempt (status and validity) into Google Sheets.
  Uses Wait nodes and batching to avoid API rate limits.

  Key Features
  Trigger-based automation (WooCommerce trigger; adaptable to Shopify webhook).
  Batch processing using SplitInBatches for stable throughput.
  Phone number cleaning using JavaScript (waNoStr.replace(/\D/g, "")).
  Pre-send WhatsApp verification via Rapiwa to reduce failed sends.
  Conditional branching (IF node) between verified and unverified flows.
  Personalized message templates that include product and customer fields.
  Logging to Google Sheets with separate flows for verified/sent and unverified/not sent.
  Wait node for throttling and looping control.

  Requirements
  Running n8n instance with nodes: HTTP Request, Code, SplitInBatches, IF, Google Sheets, Wait, and a WooCommerce trigger (or equivalent).
  Rapiwa account and Bearer token for verify/send endpoints.
  Google account and Google Sheets access with OAuth2 credentials.
  WooCommerce store access credentials (or Shopify credentials if adapting).
  Incoming order payloads containing billing and line_items fields.

  Google Sheet format (example rows)
  A Google Sheet formatted like this ➤ Sample

  | Customer Name  | Phone Number  | Email Address     | Address     | Product Title    | Product ID | Size | Quantity | Total Price | Product Image                                                                                                                              | Invoice Link                                                                                                                                                                                           | Status   | Validity   |
  | -------------- | ------------- | --------------------------------------------------------------------- | ----------- | ------------------------------------ | ---------- | ---- | -------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------- | ---------- |
  | Abdul Mannan| 8801322827799 | contact@spagreen.net | mirpur| T-Shirt - XL | 110        | XL   | 1        | BDT 499.00  | https://your_shop_domain/Product/gg.img | https://your_shop_domain/INV/DAS | sent     | verified   |
  | Abdul Mannan| 8801322827799 | contact@spagreen.net | mirpur| T-Shirt - XL | 110        | XL   | 1        | BDT 499.00  | https://your_shop_domain/Product/gg.img | https://your_shop_domain/INV/DAS | not sent | unverified |

  Important Notes
  The Code nodes assume billing and line_items exist in the incoming payload; update mappings if your source differs.
  The message template references products[0]; if orders contain multiple items, update logic to summarize or iterate products.
  Start testing with small batches to avoid accidental mass messaging and to respect Rapiwa rate limits.

  Useful Links
  Dashboard:** https://app.rapiwa.com
  Official Website:** https://rapiwa.com
  Documentation:** https://docs.rapiwa.com

  Support & Help
  WhatsApp**: Chat on WhatsApp
  Discord**: SpaGreen Community
  Facebook Group**: SpaGreen Support
  Website**: https://spagreen.net
  Developer Portfolio**: Codecanyon SpaGreen

nodes_used:
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workflow_json_compressed:
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name: WooCommerce Order Updates to Customers via WhatsApp with Rapiwa API
author_name: Rapiwa
author_username: rapiwa
categories: []
created_at: 2025-10-19T05:34:31.088Z
updated_at: 2025-10-19T05:34:31.088Z
url: https://n8n.io/workflows/9880
scraped_at: 2025-12-24 13:02:45
description:
  Who is this for?
  This workflow is for online store owners, support teams, and marketing staff who want to automatically verify WhatsApp numbers and send order invoice links or personalized order updates to customers. It’s built against WooCommerce order webhooks but can be adapted to Shopify or other e-commerce platforms that provide billing and line_items.

  What this Workflow Does
  Receives order events (Webhook / WooCommerce order.updated).
  Normalizes the payload into a compact object: { data: { customer, products, invoice_link } } via a Code node.
  Iterates items in batches (SplitInBatches) to control throughput.
  Cleans phone numbers (removes non-digits) and verifies WhatsApp registration using Rapiwa (/api/verify-whatsapp).
  Sends templated WhatsApp messages through Rapiwa (/api/send-message) for verified numbers.
  Logs every attempt into Google Sheets: one sheet for verified & sent rows, another for unverified & not sent rows.
  Uses a Wait node to throttle and loop back into the batch processor.

  Key Features
  Trigger-based automation (Webhook or WooCommerce trigger).
  Payload normalization and mapping via JavaScript Code nodes.
  Controlled batching (SplitInBatches) to avoid rate limits.
  Pre-send verification of WhatsApp numbers using Rapiwa.
  Conditional branching with the IF node to separate verified vs unverified flows.
  Personalized message templates that pull customer and product fields from the mapped data.
  Logging and audit trail stored in Google Sheets (two separate append flows).

  How to Use — Step-by-step Setup
  Add credentials in n8n
     Rapiwa: Create an HTTP Bearer credential and paste your Bearer token (example name used in the flow: Rapiwa Bearer Auth).
     Google Sheets: Create an OAuth2 credential (example: Google Sheets).
     WooCommerce: Add WooCommerce API credentials for the trigger (or configure Shopify credentials if adapting).

  Import / configure nodes in n8n
     Webhook (or WooCommerce Trigger): receive order payloads. Example Webhook path is present in the exported flow.
     Code node Format Webhook Response Data: map body.billing, body.line_items, body.payment_url into { data: { customer, products, invoice_link } }.
     Code node Clean WhatsApp Number: ensure the phone number is a string and strip non-digits: String(rawNumber).replace(/\D/g, "").
     HTTP Request Check valid whatsapp number Using Rapiwa: POST to https://app.rapiwa.com/api/verify-whatsapp with { number }. Use the Rapiwa Bearer credential.
     IF If: check verification result. The flow compares {{$json.data.exists}} to "true" in the exported flow; normalize types if your API returns booleans.
     HTTP Request Rapiwa Sender: POST to https://app.rapiwa.com/api/send-message with number, message_type: 'text', and a templated message (see message template in the flow).
     Google Sheets Store State of Rows in Verified & Sent and Store State of Rows in Unverified & Not Sent

  Google Sheet Column Structure
  Create these columns exactly (the Google Sheets nodes in the flow expect these names):
  A Google Sheet formatted like this ➤ sample

  | Name            | Number        | Email             | Address      | Product Title                                  | Product ID | Size | Quantity | Total Price   | Product Image                                                                 | Invoice Link                                                                                             | Product Status | Validity   | Status   |
  |-----------------|---------------|-------------------|--------------|------------------------------------------------|------------|------|----------|----------------|--------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|----------------|------------|----------|
  | Abdul Mannan  | 8801322827799 | contact@spagreen.net   | mirpur dohs  | Air Force 1 Reigning Champ Dark Grey 1:1 - 40 | 251        | 40   | 1        | BDT 5800.00    |         | Invoice | on-hold        | verified   | sent     |
  | Abdul Mannan  | 8801322827799 | contact@spagreen.net   | mirpur dohs  | Air Force 1 Reigning Champ Dark Grey 1:1 - 40 | 251        | 40   | 1        | BDT 5800.00    |         | Invoice | on-hold        | unverified | not sent |

  Customization Ideas
  Adapt the Code mapping node for Shopify payloads or other marketplaces.
  Iterate and include multiple products in the message instead of using products[0].
  Add filters in the Code node (e.g., only process orders with total &gt; 5000).
  Add fallback channels (SMS or email) for unverified numbers.
  Persist logs into a database for analytics and retention beyond Google Sheets.
  Add admin notifications (Slack, email) at the end of each run.

  Useful Links
  Dashboard:** https://app.rapiwa.com
  Official Website:** https://rapiwa.com
  Documentation:** https://docs.rapiwa.com

  Support & Help
  WhatsApp**: Chat on WhatsApp
  Discord**: SpaGreen Community
  Facebook Group**: SpaGreen Support
  Website**: https://spagreen.net
  Developer Portfolio**: Codecanyon SpaGreen

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.webhook","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-rapiwa.rapiwa","n8n-nodes-rapiwa.rapiwa"]

workflow_json_compressed:
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name: Generate Personalized Cold Email Icebreakers from sites with GPT-4 & G-Sheets
author_name: Mirai
author_username: mirai
categories: []
created_at: 2025-10-19T08:34:16.229Z
updated_at: 2025-10-19T08:34:16.229Z
url: https://n8n.io/workflows/9882
scraped_at: 2025-12-24 13:02:42
description:
  Icebreaker Generator powered with ChatGPT 

  This n8n template crawls a company website, distills the content with AI, and produces a short, personalized icebreaker you can drop straight into your cold emails or CRM. Perfect for SDRs, founders, and agencies who want “real research” at scale.

  Good to know

  Works from a Google Sheet of leads (domain + LinkedIn, etc.).

  Handles common scrape failures gracefully and marks the lead’s Status as Error.

  Uses ChatGPT to summarize pages and craft one concise, non-generic opener.

  Output is written back to the same Google Sheet (IceBreaker, Status).

  You’ll need Google credentials (for Sheets) and OpenAI credentials (for GPT).

  How it works

  Step 1 — Discover internal pages

  Reads a lead’s website from Google Sheets.

  Scrapes the home page and extracts all links.

  A Code node cleans the list (removes emails/anchors/social/external domains, normalizes paths, de-duplicates) and returns unique internal URLs.

  If the home page is unreachable or no links are found, the lead is marked Error and the workflow moves on.

  Step 2 — Convert pages to text

  Visits each collected URL and converts the response into HTML/Markdown text for analysis.

  You can cap depth/amount with the Limit node.

  Step 3 — Summarize & generate the icebreaker

  A GPT node produces a two-paragraph abstract for each page (JSON output).

  An Aggregate node merges all abstracts for the company.

  Another GPT node turns the merged summary into a personalized, multi-line icebreaker (spartan tone, non-obvious details).

  The result is written back to Google Sheets (IceBreaker = ..., Status = Done).

  The workflow loops to the next lead.

  How to use

  Prepare your sheet

  Include at least: organization_website_url, linkedin_url, and any other lead fields you track.

  Keep an empty IceBreaker and Status column for the workflow to fill.

  Connect credentials

  Google Sheets: use the Google account that owns the sheet and link it in the nodes.

  OpenAI: add your API key to the GPT nodes (“Summarize Website Page”, “Generate Multiline Icebreaker”).

  Run the workflow

  Start with the Manual Trigger (or replace with a schedule/webhook).

  Adjust Limit if you want fewer/more pages per company.

  Watch Status (Done/Error) and IceBreaker populate in your sheet.

  Requirements

  n8n instance

  Google Sheets account & access to the leads sheet

  OpenAI API key (for summarization + icebreaker generation)

  Customizing this workflow

  Tone & format: tweak the prompts (both GPT nodes) to match your brand voice and structure.

  Depth: change the Limit node to scan more/less pages; add simple rules to prioritize certain paths (e.g., /about, /blog/*).

  Fields: write additional outputs (e.g., Company Summary, Key Products, Recent News) back to new sheet columns.

  Lead selection: filter rows by Status = "" (or custom flags) to only process untouched leads.

  Error handling: expand the Error branch to retry with www./HTTP→HTTPS or to log diagnostics in a separate tab.

  Tips

  Keep icebreakers short, specific, and free of clichés—small, non-obvious details from the site convert best.

  Start with a small batch to validate quality, then scale up.

  Consider adding a rate limit if target sites throttle requests.

  In short: Sheet → crawl internal pages → AI abstracts → single tailored icebreaker → write back to the sheet, then repeat for the next lead.

  This automation can work great with our automation for automated cold emailing.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.html","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.markdown","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.limit","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Automated B2B Lead Generation: Google Maps to Sheets with BrowserAct & Telegram
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2025-10-19T10:50:25.523Z
updated_at: 2025-10-19T10:50:25.523Z
url: https://n8n.io/workflows/9890
scraped_at: 2025-12-24 13:02:41
description:
  Automated B2B Lead Generation from Google Maps to Google Sheets using BrowserAct

  This n8n template automates local lead generation by scraping Google Maps for businesses, saving them to Google Sheets, and notifying you in real-time via Telegram.

  This workflow is perfect for sales teams, marketing agencies, and local B2B services looking to build targeted lead lists automatically.

  Self-Hosted Only 
  This Workflow uses a community contribution and is designed and tested for self-hosted n8n instances only.

  How it works
  The workflow is triggered manually. You can set the Location, Bussines_Category, and number of leads (Extracted_Data) in the first BrowserAct node.
  A BrowserAct node ("Run a workflow task") initiates the scraping job on Google Maps using your specified criteria.
  A second BrowserAct node ("Get details of a workflow task") pauses the workflow and waits for the scraping task to be 100% complete.
  A Code node takes the raw JSON string output from the scraper and correctly parses it, splitting the data into individual items (one for each business).
  A Google Sheets node appends or updates each lead into your spreadsheet, matching on the "Name" column to prevent duplicate entries.
  Finally, a Telegram node sends a message with the new lead's details to your specified chat, providing instant notification.

  Requirements
  BrowserAct** API account for web scraping
  BrowserAct* "Google Maps Local Lead Finder*" Template
  BrowserAct** n8n Community Node -&gt; (n8n Nodes BrowserAct)
  Google Sheets** credentials for saving leads
  Telegram** credentials for sending notifications

  Need Help?
  How to Find Your BrowseAct API Key & Workflow ID
  How to Connect n8n to Browseract
  How to Use & Customize BrowserAct Templates
  How to Use the BrowserAct N8N Community Node

  Workflow Guidance and Showcase

  AUTOMATE Local Lead Generation: Google Maps to Sheets & Telegram with n8n

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-browseract-workflows.browserAct","n8n-nodes-browseract-workflows.browserAct","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","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.stickyNote","n8n-nodes-base.stickyNote"]

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name: Monitor Shopify Stores for New Products with BrowserAct and Slack Alerts
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2025-10-19T11:38:20.554Z
updated_at: 2025-10-19T11:38:20.554Z
url: https://n8n.io/workflows/9895
scraped_at: 2025-12-24 13:02:41
description:
  Automated E-commerce Store Monitoring for New Products Using BrowserAct

  This n8n template is an advanced competitive intelligence tool that automatically monitors competitor E-commerce/Shopify stores and alerts you the moment they launch a new product.

  This workflow is essential for e-commerce store owners, product strategists, and marketing teams who need real-time insight into what their competitors are selling.

  Self-Hosted Only 
  This Workflow uses a community contribution and is designed and tested for self-hosted n8n instances only.

  How it works
  The workflow runs on a Schedule Trigger to check for new products automatically (e.g., daily).
  A Google Sheets node fetches your master list of competitor store links from a central sheet.
  The workflow loops through each competitor one by one.
  For each competitor, a Google Sheets node first creates a dedicated tracking sheet (if one doesn't exist) to store their product list history.
  A BrowserAct node then scrapes the competitor's current product list from their live website.
  The scraped data is saved to the competitor's dedicated tracking sheet.
  The workflow then fetches the newly scraped list and the previously stored list of products.
  A custom Code node (labeled "Compare Datas") performs a difference check to reliably detect if any new products have been added.
  If a new product is detected, an If node triggers an immediate Slack alert to your team, providing real-time competitive insight.

  Requirements
  BrowserAct** API account for web scraping
  BrowserAct* "Competitors Shopify Website New Product Monitor*" Template
  BrowserAct** n8n Community Node -&gt; (n8n Nodes BrowserAct)
  Google Sheets** credentials for storing and managing data
  Slack** credentials for sending alerts

  Need Help?
  How to Find Your BrowseAct API Key & Workflow ID
  How to Connect n8n to Browseract
  How to Use & Customize BrowserAct Templates
  How to Use the BrowserAct N8N Community Node

  Workflow Guidance and Showcase

  Automatically Track Competitor Products | n8n & Google Sheets Template

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.merge","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.code","n8n-nodes-base.code","n8n-nodes-browseract-workflows.browserAct","n8n-nodes-browseract-workflows.browserAct","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Summarize & Extract Glassdoor Company Info with Google Gemini and Decodo
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-10-20T03:38:49.348Z
updated_at: 2025-10-20T03:38:49.348Z
url: https://n8n.io/workflows/9924
scraped_at: 2025-12-24 13:02:46
description:
  This workflow automates company research and intelligence extraction from Glassdoor using Decode API for data retrieval and Google Gemini for AI-powered summarization.

  Who this is for

  This workflow is ideal for:

  Recruiters, analysts, and market researchers looking for structured insights from company profiles.
  HR tech developers and AI research teams needing a reliable way to extract and summarize Glassdoor data automatically.
  Venture analysts or due diligence teams conducting company research combining structured and unstructured content.
  Anyone who wants instant summaries and insights from Glassdoor company pages without manual scraping.

  What problem this workflow solves

  Manual Data Extraction**: Glassdoor company details and reviews are often scattered and inconsistent, requiring time-consuming copy-paste efforts.
  Unstructured Insights**: Raw reviews contain valuable opinions but are not organized for analytical use.
  Fragmented Company Data**: Key metrics like ratings, pros/cons, and FAQs are mixed with irrelevant data.
  Need for AI Summarization**: Business users need a concise, executive-level summary that combines employee sentiment, culture, and overall performance metrics.

  This workflow automates data mining, summarization, and structuring, transforming Glassdoor data into ready-to-use JSON and Markdown summaries.

  What this workflow does

  The workflow automates the end-to-end pipeline for Glassdoor company research:

  Trigger

     Start manually by clicking “Execute Workflow.”

  Set Input Fields

     Define company_url (e.g., a Glassdoor company profile link) and geo (country).

  Extract Raw Data from Glassdoor (Decodo Node)

     Uses the Decodo API to fetch company data — including overview, ratings, reviews, and frequently asked questions.

  Generate Structured Data (Google Gemini + Output Parser)

     The Structured Data Extractor node (powered by Gemini AI) processes raw data into well-defined fields:

       Company overview (name, size, website, type)
       Ratings breakdown
       Review snippets (pros, cons, roles)
       FAQs
       Key takeaways

  Summarize the Insights (Gemini AI Summarizer)

     Produces a detailed summary highlighting:

       Company reputation
       Work culture
       Employee sentiment trends
       Strengths and weaknesses
       Hiring recommendations

  Merge and Format

     Combines structured data and summary into a unified object for output.

  Export and Save

     Converts the final report into JSON and writes it to disk as
       C:\{{CompanyName}}.json.

  Binary Encoding for File Handling

     Prepares data in base64 for easy integration with APIs or downloadable reports.

  Setup

  Prerequisites

  n8n instance** (cloud or self-hosted)
  Decodo API credentials** (added as decodoApi)
  Google Gemini (PaLM) API credentials**
  Access to the Glassdoor company URLs

  Make sure to install the Decodo Community Node.

  Steps

  Import this workflow JSON file into your n8n instance.
  Configure your credentials for:

     Decodo API
     Google Gemini (PaLM) API
  Open the Set the Input Fields node and replace:

     company_url → with the Glassdoor URL
     geo → with the region (e.g., India, US, etc.)
  Execute the workflow.
  Check your output folder (C:\) for the exported JSON report.

  How to Customize This Workflow

  You can easily adapt this template to your needs:

  Add Sentiment Analysis**

    Include another Gemini or OpenAI node to rate sentiment (positive/negative/neutral) per review.
  Export to Notion or Google Sheets**

    Replace the file node with a Notion or Sheets integration for live dashboarding.
  Multi-Company Batch Mode**

    Convert the manual trigger to a spreadsheet or webhook trigger for bulk research automation.
  Add Visualization Layer**

    Connect the output to Looker Studio or Power BI for analytical dashboards.
  Change Output Format**

    Modify the final write node to generate Markdown or PDF summaries using the pypandoc or reportlab module.

  Summary

  This n8n workflow combines Decode web scrapping with Google Gemini’s reasoning and summarization power to build a fully automated Glassdoor Research Engine.

  With a single execution, it:

  Extracts structured company details
  Summarizes thousands of employee reviews
  Delivers insights in an easy-to-consume format

  Ideal for:

  Recruitment intelligence
  Market research
  Employer branding
  Competitive HR analysis

nodes_used:
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