# templates

name: Extract Contacts from Business Cards to Google Sheets With GPT4o
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T06:44:32.114Z
updated_at: 2025-08-02T06:44:32.114Z
url: https://n8n.io/workflows/6840
scraped_at: 2025-12-24 13:02:43
description:
  📄 Auto Extract Contacts from Business Cards to Sheet With GPT4o

  &gt; This smart workflow extracts names, phone numbers, emails, and more from uploaded name card photos using AI, then logs them neatly into your Google Sheet. No typing. No mess. Just upload and go.

  👤 Who’s it for

  Sales & Business Development Teams  
  Recruiters & Talent Acquisition Specialists  
  Event Teams collecting business cards  
  Admins who manage contact databases manually  

  ⚙️ How it works / What it does

  This workflow automates the extraction of contact details from uploaded name card (business card) images and stores them in a structured Google Sheet for easy tracking and follow-up.

  Workflow Steps:
  User uploads one or more name card images through a web form.
  The uploaded files are saved to a Google Drive folder for archiving.
  A smart AI agent (with OCR and GPT capabilities) scans each image and extracts relevant contact data into structured JSON format.
  Data is transformed, cleaned (e.g., removing + from phone numbers), and filtered.
  Valid contacts are appended to a Google Sheet for central tracking and future use.

  🛠 How to set up

  Create a Form  
     Allow file upload (JPG/PNG format).
     Label it as “Name Card Uploader” with a clear description.

  Upload to Google Drive  
     Use the Google Drive node to store uploaded images.

  Configure Smart Agent  
     Use GPT-4o or similar model with OCR capability.
     Apply a structured output parser to extract contact fields like name, phone, email, company, etc.

  Transform Data  
     Use the Code node to clean and structure contact info.
     Strip out unwanted characters from phone numbers (e.g., +).

  Filter Invalid Records  
     Remove entries with no meaningful contact data.

  Append to Google Sheets  
     Use the Google Sheets node with "Append Sheet Row".
     Map fields to columns like Name, Phone, Email, etc.

  ✅ Requirements

  n8n workflow environment  
  Google Drive integration (for file storage)  
  Google Sheets integration (for storing contacts)  
  GPT-4o or any image-capable LLM  
  Clear name card images (PNG/JPG, readable text)  
  (Optional) Slack/email integration for notifications

  🧩 How to customize the workflow

  CRM Sync**: Connect to platforms like HubSpot, Salesforce, or Zoho.  
  Validation Logic**: Ensure records contain key fields like name or email before writing.  
  Uploader Info**: Attach submitter metadata to each contact record.  
  Language Adaptation**: Adjust extracted field labels/output to target your preferred language.  
  Batch Upload**: Handle multiple cards in a single image or multiple uploads in one go.

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workflow_json_compressed:
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name: Automate weekly Hollywood film briefing via Tavily and Gemini
author_name: Manav Desai
author_username: manavdesai17
categories: []
created_at: 2025-08-02T08:23:11.194Z
updated_at: 2025-08-02T08:23:11.194Z
url: https://n8n.io/workflows/6841
scraped_at: 2025-12-24 13:02:41
description:
  This n8n template demonstrates how to build a weekly Hollywood film industry briefing using Tavily for real-time search and Google Gemini for summarization. It sends a concise, emoji‑styled email with movie releases, box office results, industry news, and must‑watch recommendations every week automatically.

  Use cases: Great for film journalists, entertainment bloggers, or movie enthusiasts who want automated weekly updates without manually checking multiple sources.

  Good to know

  Free to use: Tavily provides **1,000 API credits per month on their free plan (no credit card required), so this workflow can run at zero cost.
  Real-time data**: Tavily’s search API is optimized for up-to-date information — perfect for weekly movie releases and box office stats.
  Google Gemini is used for summarization, and you only need basic API access (no paid tier required).

  How it works

  Trigger**: Scheduled every Thursday morning (configurable).
  Search**: Four Tavily API calls gather:

    Movies releasing this week
    Last week’s box office results
    Hollywood industry news
    Must‑watch movies currently in theatres
  Summarization**: Google Gemini turns this into Gmail‑friendly HTML with emojis and bullet points.
  Email**: The formatted newsletter is sent via Gmail node.

  How to use

  Configure Tavily API and Gmail OAuth2 credentials in n8n’s credential manager.
  (Optional) Edit Tavily queries to focus on specific genres or add filters.
  Adjust the schedule trigger to any day/time you prefer.

  Requirements

  Tavily API account (free plan – 1,000 monthly requests)
  Google Gemini API key for summarization
  Gmail account (OAuth2 credentials for sending emails)

  Want insane output quality?

  You can swap Gemini for OpenAI’s ChatGPT models:

  GPT‑3.5 Turbo** – \~\$0.002/run (crazy cheap)
  GPT‑4o** – \~\$0.009/run (latte price)
  GPT‑4.5** – \~\$0.15/run (god‑mode quality)

  This upgrade gives you cleaner, richer, “did‑a‑human‑write‑this?” vibes — perfect for journalist‑grade Hollywood briefings. Just note: OpenAI API requires a \$5 minimum credit to activate usage.

  Example Output (ChatGPT version)

  Subject: Daily Hollywood Film Industry Briefing – August 3, 2025

  Good morning,
  Here's your daily Hollywood film briefing for August 3, 2025:

  🎬 Releases

  The Bad Guys 2 – Released Friday, August 1, 2025
  The Naked Gun – Released Friday, August 1, 2025

  These are the confirmed new wide theatrical Hollywood releases this week (Monday through Sunday of current week). No additional new Hollywood theatrical releases found for this week.

  📊 Box Office

  Highest‑grossing Hollywood films of 2025 (worldwide):

  Ne Zha 2 – approx. \$1.90 billion (non‑Hollywood Chinese animated film leads)
  Lilo & Stitch – approx. \$1.02 billion
  A Minecraft Movie – approx. \$955 million
  Jurassic World Rebirth – approx. \$731 million
  How to Train Your Dragon – approx. \$610 million

  Last week’s box office performance (Monday–Sunday):

  The Fantastic Four: First Steps – domestic debut \\$118 M; global \\$218 M, Marvel’s biggest opening of 2025
  Superman – added \~\$94 M worldwide last week, passing \$500 M global total
  Jurassic World Rebirth – up \\$70 M worldwide last week, despite \40 % drop week‑on‑week
  F1: The Movie – up \~\$48 M last week internationally/domestically growth visible
  Lilo & Stitch – added \~\$10 M worldwide last week, slower tail but still billion‑plus gross

  Highlights & trends:
  Fantastic Four’s strong debut reboots Marvel success, signaling resumed audience interest; Superman continues to hold strong; Jurassic World Rebirth remains durable after holiday surge; surge in box office recovery noted across key titles. Overall box office up \~12–15 % year‑on‑year.

  📰 Industry Buzz

  Christopher Nolan has signed to direct a massive \$250 million adaptation of Homer’s The Odyssey, starring Matt Damon and Tom Holland, with Imax pre‑sales at 95 % capacity across major locations.
  Marvel has relaunched the Fantastic Four franchise successfully with First Steps; positive CinemaScore and strong visuals marking a fresh start.
  DC’s Superman continues strong with over \$500 M global, solidifying DC’s summer comeback.
  Universal’s Jurassic World Rebirth continues strong overseas, especially in China, contributing to \$318 M global in opening holiday weekend.
  Warner Bros.–Discovery stock surges (\~30 %) amid box office rebound, with Disney, IMAX and Cinemark also seeing robust growth in 2025.
  Ne Zha 2 becomes highest‑grossing animated and non‑Hollywood film ever, crossing \$2 billion globally—though not Hollywood, its impact on global trends is notable.
  Mission: Impossible – The Final Reckoning quietly solidifies strong global numbers (\~\$562 M) and continues reliable franchise performance.

  🎥 Must‑Watch in Theatres (Surat, India)

  The Fantastic Four: First Steps** – Currently showing in English/Hindi/Tamil/Telugu in Surat cinemas; hyped globally, strong visuals, action‑heavy, best experienced in IMAX or premium formats if available in Surat multiplexes. Runs this week.
  F1: The Movie** – Available in Surat in multiple languages, strong reviews praising adrenaline‑fuelled direction and visuals and growing fan hype; ideal in standard or Dolby formats for immersive sound and speed feel.
  Jurassic World Rebirth** – Still playing in Surat, popular with family audiences; grand visuals and dinosaur action well‑suited to IMAX or large format screens.

  That’s all for today’s briefing. Have a great theatrical weekend ahead!

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workflow_json_compressed:
  [encoded data, 9216 characters]


name: Manage Cloudflare DNS Records with AI-powered Chat Assistant
author_name: KPendic
author_username: kres
categories: []
created_at: 2025-08-02T10:45:57.207Z
updated_at: 2025-08-02T10:45:57.207Z
url: https://n8n.io/workflows/6844
scraped_at: 2025-12-24 13:02:41
description:
  This n8n flow demos basic dev-ops operation task, dns records management. 

  AI agent with light and basic prompt functions like getter and setter for DNS records. 

  In this special case, we are managing remote dns server, via API calls - that are handled on CloudFlare platform side.

  Use-cases for this flow can be standalone, or you can chain it in your pipe-line to get powerful infrastructure flows for your needs.

  How it works

  we created basic agent and gave it a prompt to know about one tool: cf_tool - sub-routine (to itself flow - or it can be separate dedicated one)
  prompt have defined arguments that are needed for passing them when calling agent, for each action specifically
  tool it self have basic if switch that is - based of a action call - calling specific CloudFlare API endpoint (and pass down the args from the tool)

  Requirements

  For storing and processing of data in this flow you will need:

  CloudFlare.com API key/token - for retrieving your data (https://dash.cloudflare.com/?to=/:account/api-tokens)
  OpenAPI credentials (or any other LLM provider) saved - for agent chat
  (Optional) PostGres table for chat history saving

  Official CloudFlare api Documentation

  For full details and specifications please use API documentation from: https://developers.cloudflare.com/api/

  Linkedin post

  Let me know if you found this flow usefull on my Linkedin post &gt; here.

  tags: #cloudflare, #dns, #domain

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  [encoded data, 4476 characters]


name: Generate Animated Human Videos from Images & Audio with Bytedance Omni Human
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T12:19:24.841Z
updated_at: 2025-08-02T12:19:24.841Z
url: https://n8n.io/workflows/6876
scraped_at: 2025-12-24 13:02:44
description:
  Generate Animated Human Videos from Images & Audio with Bytedance Omni Human

  Built with n8n + Replicate

  This workflow takes an image + audio, sends them to Bytedance’s omni-human model, waits for processing, and returns a generated video.

  ⚡ Section 1: Start & Authenticate

  ▶️ On clicking ‘execute’** → Manual trigger to start the workflow.
  🔑 Set API Key** → Stores your Replicate API key so future requests are authorized.

  Benefit: Secures your API credentials in one place for easy re-use.

  🛠️ Section 2: Send Video Generation Request

  📡 Create Prediction** → Makes a POST request to Replicate with:

    image: input image URL
    audio: input audio URL
    Model version: 7ec44f5140c7338b3496cbf99ee8ea391a4bc18ff5d1677a146dfc936a91f65b

  Benefit: Combines visual and audio inputs to start AI-powered video generation.

  🔍 Section 3: Track the Prediction

  📦 Extract Prediction ID** → Saves predictionId, status, and predictionUrl for polling.
  ⏳ Wait** → Pauses 2 seconds between status checks (to avoid spamming the API).
  🔁 Check Prediction Status** → Queries Replicate using the stored prediction URL.
  ✅ Check If Complete** → Branches:

    If status = succeeded → move forward.
    Else → loop back to Wait until completion.

  Benefit: Ensures workflow patiently waits for the video instead of timing out.

  📽️ Section 4: Process & Return Results

  📦 Process Result** → Cleans the API response, returning:

    status
    video_url (generated video)
    metrics
    created_at & completed_at
    model: bytedance/omni-human

  Benefit: Gives you a neat, structured output with the generated video link ready to use.

  📊 Workflow Overview

  | Section             | Purpose                     | Key Nodes                                     | Benefit                          |
  | ------------------- | --------------------------- | --------------------------------------------- | -------------------------------- |
  | ⚡ Start & Auth      | Initialize & secure API key | Manual Trigger, Set API Key                   | Keeps credentials safe           |
  | 🛠️ Send Request    | Start video generation      | Create Prediction                             | Submits image+audio to Replicate |
  | 🔍 Track Prediction | Poll status until done      | Extract Prediction ID, Wait, Check Status, If | Reliable async handling          |
  | 📽️ Process Result  | Format output               | Process Result                                | Easy access to final video link  |

  ✅ Final Benefits

  🎬 Turns static image + audio into full AI-generated video.
  🔑 API key stored securely in workflow.
  🔄 Handles async generation with auto-polling.
  📤 Outputs clean JSON with direct video link.
  🧩 Modular — you can connect results to Slack, Gmail, or Google Drive for auto-sharing.

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workflow_json_compressed:
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name: Convert Multiple Files to Base64 with JavaScript Code
author_name: Viktor Klepikovskyi
author_username: vklepikovskyi
categories: []
created_at: 2025-08-02T12:39:55.614Z
updated_at: 2025-08-02T12:39:55.614Z
url: https://n8n.io/workflows/6885
scraped_at: 2025-12-24 13:02:45
description:
  Base64 Encode Multiple Binary Files with a Code Node
  This template demonstrates how to handle multiple binary files in n8n by using a Code node to convert them into a Base64 encoded string. It's particularly useful when an API requires file uploads in this format and the standard 'Extract From File' node is not sufficient for batch processing. The workflow starts by downloading a ZIP file, unzipping it to get multiple binary files, and then uses a Code node with custom JavaScript to encode each file individually.
  Instructions
  Download and import this template into your n8n instance.
  Run the workflow once to see how it downloads, unzips, and then encodes multiple files.
  Modify the 'HTTP Request' node to download your own binary file or a ZIP file containing multiple files.
  Update the 'Code' node if you need to adjust the output format or file paths.
  Use the output of the 'Code' node in a subsequent node, such as another 'HTTP Request' to send the Base64-encoded files to your desired API.

  A link to the full blog post is available here.

nodes_used:
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name: Enhance AI Chatbot Responses with InfraNodus Knowledge Graph Reasoning
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-08-02T13:49:53.846Z
updated_at: 2025-08-02T13:49:53.846Z
url: https://n8n.io/workflows/6887
scraped_at: 2025-12-24 13:02:46
description:
  Augment AI chatbot prompts with a knowledge graph reasoning ontology and improve the quality of responses with Graph RAG.

  In this workflow, we augment the original prompt using the InfraNodus GraphRAG system that will extract a reasoning ontology from a graph that you create (or that you can copy from our repository of public graphs). 

  This additional reasoning logic will improve the user's prompt and make it more descriptive and closely related to the logic you want to use. 

  As the next step, you can send it back to the same graph to generate a high-quality response using Graph RAG or to another graph (or AI model) to apply one type of knowledge in a completely different field.

  How it works

  Receives a request from a user (via n8n or a publicly available URL chat bot, you can also connect it to Telegram
  Sends the request to the knowledge graph in your InfraNodus account that contains a reasoning ontology represented as a knowledge graph. Reformulates the original prompt to include the reasoning logic provided. 
  Sends the request to the knowledge graph in your InfraNodus account (same as the previous one or a new one for cross-disciplinary research) to retrieve a high-quality response using GraphRAG

  Special sauce: InfraNodus will build a graph from your augmented prompt, then overlap it on the knowledge graph you want to inquire, traverse this graph based on the overlapped parts and extended relations, then retrieve the necessary part of the graph and include it in the context to improve the quality of your response. This helps InfraNodus grasp the relations and nuances that are not usually available through standard RAG.

  How to use

  • Just get an InfraNodus API key and add it into your Prompt Augmentation and Knowledge Base InfraNodus HTTP nodes for authentication

  • Then provide the name of the graphs you want to be using for prompt augmentation and retrieval. Note, these can be two different graphs if you want to apply a reasoning logic from one domain in another (e.g. machine learning in biology or philosophy in electrical engineering).

  Support

  If you wan to create your own reasoning ontology graphs, please, refer to this article on generating your own knowledge graph ontologies.

  You may also be interested to watch this video that explains the logic of this approach in detail:



  Help article on the same topic: Using knowledge graphs as reasoning experts. 

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name: Generate High-Quality Audio with Voxtral Small 24B 2507
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T14:22:43.454Z
updated_at: 2025-08-02T14:22:43.454Z
url: https://n8n.io/workflows/6890
scraped_at: 2025-12-24 13:02:45
description:
  Generate High-Quality Audio with Voxtral Small 24B 2507

  This workflow integrates the notdaniel/voxtral-small-24b-2507 model from Replicate to generate audio content from provided inputs. It handles API authentication, creates predictions, polls until completion, and outputs the final generated audio file.

  ⚡ Section 1: Trigger & Authentication

  🔘 On clicking 'execute'** → Manually starts the workflow.
  🔑 Set API Key** → Stores your Replicate API key to authenticate requests.

  Benefit: Securely connects your workflow to Replicate’s API and ensures only authorized requests are made.

  🎛️ Section 2: Create Prediction

  🌐 Create Prediction** → Sends a request to Replicate’s API with parameters like:

    audio: Input audio file (e.g., a reference sample).
    max\_new\_tokens: Maximum number of tokens to generate (controls audio length/complexity).

  Benefit: Starts the audio generation process with configurable input and settings.

  ⏳ Section 3: Polling & Status Tracking

  🆔 Extract Prediction ID** → Captures the unique prediction ID and endpoint for polling.
  ⏱️ Wait** → Pauses for 2 seconds before re-checking.
  📡 Check Prediction Status** → Polls Replicate’s API to see if the audio generation is done.
  ✅ Check If Complete** →

    If finished: moves forward to process results.
    If not: loops back to wait and check again.

  Benefit: Efficiently manages asynchronous audio generation, ensuring the workflow only proceeds when results are ready.

  🎧 Section 4: Process Result

  📝 Process Result** → Extracts and structures final output data:

    status (success or failure)
    output (raw response)
    metrics (generation statistics)
    timestamps (created and completed times)
    audio\_url (final generated audio link)

  Benefit: Provides a clean, structured output that can be used in follow-up automations (e.g., sending audio to users, storing in a database, or sharing via email).

  📊 Workflow Overview

  | Section                     | Purpose                         | Key Nodes                                                               | Benefit                          |
  | --------------------------- | ------------------------------- | ----------------------------------------------------------------------- | -------------------------------- |
  | ⚡ Trigger & Authentication  | Start workflow & authenticate   | Manual Trigger, Set API Key                                             | Secure execution                 |
  | 🎛️ Create Prediction       | Submit audio generation request | Create Prediction                                                       | Start model processing           |
  | ⏳ Polling & Status Tracking | Monitor prediction progress     | Extract Prediction ID, Wait, Check Prediction Status, Check If Complete | Ensures reliable completion      |
  | 🎧 Process Result           | Format and deliver output       | Process Result                                                          | Clean audio result ready for use |

  ✅ Final Benefits

  🔒 Secure authentication with Replicate
  🎛️ Flexible audio generation using voxtral-small-24b-2507
  ⏳ Reliable polling until results are ready
  🎧 Clean and structured audio output

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name: Automated Trip Expense Claim Form With OpenAI Agent & Google Drive
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T15:21:04.891Z
updated_at: 2025-08-02T15:21:04.891Z
url: https://n8n.io/workflows/6896
scraped_at: 2025-12-24 13:02:45
description:
  🧾 Automated Trip Expense Claim Form With OpenAI Agent & Google Drive
  Watch the demo video below:

  &gt; This workflow is designed for employees who need to submit expense claims for business trips. It automates the process of extracting data from receipts/invoices, logging it to a Google Sheet, and notifying the finance team via email.
  👤 Who’s it for
  Ideal users:
  Employees submitting business trip expense claims
  HR or Admins reviewing travel-related reimbursements
  Finance teams responsible for processing claims

  ⚙️ How it works / What it does

  Employee submits a form with trip information (name, department, purpose, dates) and uploads one or more receipts/invoices (PDF).
  Uploaded files are saved to Google Drive for record-keeping.
  Each PDF is passed to a DocClaim Assistant agent, which uses GPT-4o and a structured parser to extract structured invoice data.
  The data is transformed and formatted into a standard JSON structure.
  Two parallel paths are followed:
     Invoice records are appended to a Google Sheet for centralized tracking.
     A detailed HTML email summarizing the trip and expenses is generated and sent to the finance department for claim processing.

  🛠 How to set up

  Create a form to capture:
     Employee Name
     Department
     Trip Purpose
     From Date / To Date
     Receipt/Invoice File Upload (multiple PDFs)

  Configure file upload node to store files in a specific Google Drive folder.

  Set up DocClaim Agent using:
     GPT-4o or any LLM with document analysis capability
     Output parser for standardizing extracted receipt data (e.g., vendor, total, tax, date)

  Transform extracted data into a structured claim record (Code Node).

  Path 1: Save records to a Google Sheet (one row per expense).

  Path 2:
     Format the employee + claim data into a dynamic HTML email
     Use Send Email node to notify the finance department (e.g., finance@yourcompany.com)

  ✅ Requirements

  n8n running with access to:
    Google Drive API (for file uploads)
    Google Sheets API (for logging expenses)
    Email node (SMTP or Gmail for sending)
  GPT-4o or equivalent LLM with document parsing ability
  PDF invoices with clear formatting
  Shared Google Sheet for claim tracking
  Optional: Shared inbox for finance team

  🧩 How to customize the workflow

  Add approval steps**: route the email to a manager before finance
  Attach original PDFs**: include uploaded files in the email as attachments
  Localize for other languages**: adapt form labels, email content, or parser prompts
  Sync to ERP or accounting system**: replace Google Sheet with QuickBooks, Xero, etc.
  Set limits/validation**: enforce max claim per trip or required fields before submission
  Auto-tag expenses**: add categories (e.g., travel, accommodation) for better reporting

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name: Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:00:37.200Z
updated_at: 2025-08-02T18:00:37.200Z
url: https://n8n.io/workflows/6906
scraped_at: 2025-12-24 13:02:42
description:
  Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team

  This workflow builds a virtual finance department inside n8n. At the center is a CFO Agent (O3 model) who acts like a strategic leader. When a financial request comes in, the CFO interprets it, decides the strategy, and delegates to the specialist agents (each powered by GPT-4.1-mini for cost efficiency).

  🟢 Section 1 – Entry & Leadership

  Nodes:

  💬 When chat message received → Entry point for user financial requests.
  💼 CFO Agent (O3) → Acts as the Chief Financial Officer. Interprets the request, decides the approach, and delegates tasks.
  💡 Think Tool → Helps the CFO brainstorm and refine financial strategies.
  🧠 OpenAI Chat Model CFO (O3) → High-level reasoning engine for strategic leadership.

  ✅ Beginner view: Think of this as your finance CEO’s desk — requests land here, the CFO figures out what needs to be done, and the right specialists are assigned.

  📊 Section 2 – Specialist Finance Agents

  Each specialist is powered by GPT-4.1-mini (fast + cost-effective).

  📈 Financial Planning Analyst → Builds budgets, forecasts, and financial models.
  📚 Accounting Specialist → Handles bookkeeping, tax prep, and compliance.
  🏦 Treasury & Cash Management Specialist → Manages liquidity, banking, and cash flow.
  📊 Financial Analyst → Runs KPI tracking, performance metrics, variance analysis.
  💼 Investment & Risk Analyst → Performs investment evaluations, capital allocation, and risk management.
  🔍 Internal Audit & Controls Specialist → Checks compliance, internal controls, and audits.

  ✅ Beginner view: This section is your finance department — every role you’d find in a real company, automated by AI.

  📋 Section 3 – Flow of Execution

  User sends a request (e.g., “Create a financial forecast for Q1 2026”).
  CFO Agent (O3) interprets it → “We need planning, analysis, and treasury.”
  Delegates tasks to the relevant specialists.
  Specialists process in parallel, generating plans, numbers, and insights.
  CFO Agent compiles and returns a comprehensive financial report.

  ✅ Beginner view: The CFO is the conductor, and the specialists are the musicians. Together, they produce the financial “symphony.”

  📊 Summary Table

  | Section                | Key Roles                                               | Model             | Purpose             | Beginner Benefit                       |
  | ---------------------- | ------------------------------------------------------- | ----------------- | ------------------- | -------------------------------------- |
  | 🟢 Entry & Leadership  | CFO Agent, Think Tool                                   | O3                | Strategic direction | Acts like a real CFO                   |
  | 📊 Finance Specialists | FP Analyst, Accounting, Treasury, FA, Investment, Audit | GPT-4.1-mini      | Specialized tasks   | Each agent = finance department role   |
  | 📋 Execution Flow      | All connected                                           | O3 + GPT-4.1-mini | Collaboration       | Output = complete financial management |

  🌟 Why This Workflow Rocks

  Full finance department in n8n**
  Strategic + execution separation** → O3 for CFO, GPT-4.1-mini for team
  Cost-optimized** → Heavy lifting done by mini models
  Scalable** → Easily add more finance roles (tax, payroll, compliance, etc.)
  Practical outputs** → Reports, budgets, risk analyses, audit notes

  👉 Example Use Case:
  “Generate a Q1 financial forecast with cash flow analysis and risk report.”

  CFO reviews request.
  Financial Planning Analyst → Budget + Forecast.
  Treasury Specialist → Cash flow modeling.
  Investment Analyst → Risk review.
  Audit Specialist → Compliance check.
  CFO delivers a packaged financial report back to you.

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name: Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:02.218Z
updated_at: 2025-08-02T18:01:02.218Z
url: https://n8n.io/workflows/6907
scraped_at: 2025-12-24 13:02:44
description:
  Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini

  🔥 Powered by OpenAI O3 & GPT-4.1-mini Multi-Agent System
  \#RevOps #n8nWorkflows #AIRevenue #OpenAI #GrowthHacking

  ⚡ Section 1: Start & Orchestrator

  💬 Chat Trigger* → Listens for revenue-related requests (e.g., *“Optimize our sales funnel”).
  🤖 CRO Agent (O3)* → Acts as the *Chief Revenue Officer**.

    Thinks strategically with the Think Node.
    Decides which specialist agents to call.
  🧠 OpenAI O3 Model** → Provides advanced reasoning for CRO decisions.

  Benefit: Central orchestration ensures every request gets a strategic, executive-level response before delegation.

  🛠️ Section 2: Specialist Agents

  Each specialist agent uses GPT-4.1-mini for fast, cost-effective execution.
  They receive the CRO’s instructions and return insights.

  📈 Sales Pipeline Analyst

     Funnel optimization, conversion tracking, bottleneck fixes.
     Outputs: Pipeline health, drop-off points, recommendations.

  🎯 Revenue Attribution Specialist

     Multi-touch attribution, ROI analysis, campaign efficiency.
     Outputs: Attribution models, marketing ROI.

  📊 Revenue Forecasting Analyst

     Predictive modeling, scenario planning, growth projections.
     Outputs: Forecast reports, “what-if” scenarios.

  ⚙️ Revenue Operations Manager

     CRM optimization, territory planning, sales automation.
     Outputs: Process improvements, efficiency boosts.

  💰 Pricing & Packaging Strategist

     Competitive pricing analysis, packaging strategy, revenue optimization.
     Outputs: Price models, package recommendations.

  🧠 Revenue Intelligence Analyst

     BI dashboards, performance tracking, KPI insights.
     Outputs: Reports with actionable intelligence.

  Benefit: Breaks complex revenue problems into specialized tasks handled by domain experts.

  🔄 Section 3: Feedback & Integration

  Each agent → sends results back to CRO Agent.
  CRO Agent → compiles a comprehensive revenue strategy.
  Can integrate with CRM, BI dashboards, or Slack/Email for delivery.

  Benefit: Clear, actionable insights delivered in one place — like having a virtual RevOps team on demand.

  📊 Workflow Overview

  | Section                 | Key Nodes                           | Purpose                                           | Benefit                              |
  | ----------------------- | ----------------------------------- | ------------------------------------------------- | ------------------------------------ |
  | ⚡ Start & Orchestration | Chat Trigger, CRO Agent, O3 Model   | Capture request & assign to CRO                   | Centralized leadership               |
  | 🛠️ Specialists         | 6 Agent Nodes + GPT-4.1-mini models | Analyze pipeline, pricing, ops, attribution, etc. | Specialized, cost-efficient insights |
  | 🔄 Feedback Loop        | CRO Agent aggregation               | Compiles strategy from multiple agents            | Unified, data-driven revenue plan    |

  💡 Use Cases

  Pipeline Optimization** → Identify bottlenecks, improve conversions.
  Attribution Modeling** → Know exactly where revenue comes from.
  Revenue Forecasting** → Plan growth scenarios and projections.
  Ops Excellence** → Automate CRM, streamline sales ops.
  Pricing Strategy** → Compete smarter with optimized pricing models.
  Revenue Intelligence** → Ongoing tracking and performance monitoring.

  💸 Cost Optimization

  O3 only for CRO decisions** → Strategic layer.
  GPT-4.1-mini for specialists** → Low-cost execution (\~90% cheaper).
  Parallel processing** → All agents can run simultaneously.

  ✅ Final Result: A virtual AI-powered RevOps team that turns any revenue-related question into a comprehensive growth strategy — instantly.

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name: Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:26.784Z
updated_at: 2025-08-02T18:01:26.784Z
url: https://n8n.io/workflows/6908
scraped_at: 2025-12-24 13:02:44
description:
  Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team

  Trigger

     When chat message received → User submits an SEO request (e.g., “Help me rank for project management software”).
     The message goes straight to the SEO Director Agent.

  SEO Director Agent (O3)

     Acts like the head of SEO strategy.
     Uses the Think node to plan and decide which specialists to call.
     Delegates tasks to relevant agents.

  Specialist Agents (GPT-4.1-mini)

     Each agent has its own OpenAI model connection for lightweight cost-efficient execution.
     Tasks include:

       Keyword Research Specialist → Keyword discovery, clustering, competitor analysis.
       SEO Content Writer → Generates optimized blog posts, landing pages, etc.
       Technical SEO Specialist → Site audit, schema markup, crawling fixes.
       Link Building Strategist → Backlink strategies, outreach campaign ideas.
       Local SEO Specialist → Local citations, GMB optimization, geo-content.
       Analytics Specialist → Reports, performance insights, ranking metrics.

  Feedback Loop

     Each agent sends results back to the SEO Director.
     Director compiles insights into a comprehensive SEO campaign plan.

  ✅ Why This Setup Works Well

  O3 Model for Director** → Handles reasoning-heavy orchestration (strategy, delegation).
  GPT-4.1-mini for Specialists** → Cheap, fast, task-specific execution.
  Parallel Execution** → All specialists can run at the same time.
  Scalable & Modular** → You can add/remove agents depending on campaign needs.
  Sticky Notes** → Already document the workflow (great for onboarding & sharing).

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name: Multi-Agent Cold Email Campaign Generator with O3 Director & GPT-4.1 Specialists
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:52.773Z
updated_at: 2025-08-02T18:01:52.773Z
url: https://n8n.io/workflows/6909
scraped_at: 2025-12-24 13:02:43
description:
  Multi-Agent Cold Email Campaign Generator with O3 Director & GPT-4.1 Specialists

  🌍 Overview

  This workflow simulates a virtual sales & marketing team where each AI agent has a role:

  A Director Agent (O3) who manages strategy.
  Multiple Specialist Agents (GPT-4.1-mini) for research, writing, personalization, deliverability, sequencing, and analytics.
  Everything is triggered automatically when a new chat message request comes in.

  🟢 Section 1: Entry & Director

  🔗 Nodes:
  1️⃣ When chat message received (Trigger)
  💬 Starts the workflow when a new request arrives (e.g., “Create a cold email campaign for SaaS CTOs”).

  2️⃣ Outreach Director Agent (O3 model)
  🎯 The “manager” agent. Decides what kind of campaign is needed and assigns tasks.

  3️⃣ Think (Planning Node)
  🧠 Helps the Director structure thoughts before delegating.

  💡 Why useful?

  Director uses O3 (strong reasoning model) only where strategy is needed → reduces cost.
  Provides a single point of control to coordinate all other agents.

  🔵 Section 2: Specialist Agents

  Each is powered by GPT-4.1-mini (cheaper + faster).

  🔍 Prospect Research Specialist → researches target companies, roles, pain points.
  ✍️ Cold Email Copywriter → drafts subject lines, hooks, and persuasive body copy.
  🎯 Personalization Specialist → inserts custom variables for each recipient.
  📅 Email Sequence Strategist → designs follow-ups, timing, nurture flows.
  📬 Email Deliverability Expert → ensures emails land in inbox, not spam.
  📊 Outreach Analytics Specialist → tracks performance, runs A/B tests, optimizes campaigns.

  💡 Why useful?

  Each agent is a specialist → just like a real marketing team.
  Parallel execution** in n8n means faster results.
  Modular → you can remove or add more specialists.

  🟣 Section 3: Execution Flow

  Request comes in via chat trigger
  Director (O3) interprets and delegates → calls specialists as tools
  Specialists generate their pieces (research → copy → personalization → sequence → deliverability → analytics)
  Director integrates results into a cohesive cold email campaign

  🟡 Section 4: Documentation & Notes

  There are two Sticky Notes inside the workflow:

  Header Note** → Support info + tutorials (YouTube & LinkedIn by Yaron Been)
  Main Note** → Full documentation (overview, use cases, cost optimization, tags)

  📊 Final Overview

  | Section        | What Happens             | Why It’s Useful             |
  | -------------- | ------------------------ | --------------------------- |
  | 🟢 Director    | Trigger + O3 strategy    | Ensures smart coordination  |
  | 🔵 Specialists | GPT-4.1-mini agents      | Faster, cheaper execution   |
  | 🟣 Flow        | Delegation + Integration | Automated campaign building |
  | 🟡 Docs        | Sticky Notes             | In-workflow guide for users |

  🚀 Benefits

  ✅ AI-powered cold email team without hiring humans
  ✅ Cost-optimized (O3 only for strategy, GPT-4.1-mini for tasks → \~90% cheaper)
  ✅ End-to-end coverage (research → writing → personalization → sequencing → analytics)
  ✅ Scalable: can run multiple campaigns in parallel
  ✅ Customizable: swap models, add tools, or expand team

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name: Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:02:16.967Z
updated_at: 2025-08-02T18:02:16.967Z
url: https://n8n.io/workflows/6910
scraped_at: 2025-12-24 13:02:45
description:
  Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents

  This n8n workflow creates a complete AI-powered content department. It starts when a chat request is received, then a Content Director Agent (powered by OpenAI O3) analyzes the request and delegates tasks to specialized agents (blogs, social, video, email, website, strategy). Each agent is powered by GPT-4.1-mini, keeping costs low and quality high.

  ✅ 📩 Section 1: Trigger & Director Setup

  ⚙️ Nodes

  1️⃣ When Chat Message Received

  What it does:** Starts the workflow whenever a user sends a content request.
  Why it’s useful:** Allows real-time or on-demand content creation from chat inputs.

  2️⃣ Content Director Agent (O3)

  What it does:** Analyzes user request, defines the best content mix, and delegates tasks to specialist agents.
  Why it’s useful:** Keeps your brand voice consistent and ensures all channels align to a unified content strategy.

  💡 Beginner Benefit

  ✅ Single entry point → just type your content idea once
  ✅ AI Director coordinates everything for you
  ✅ No need to manage multiple tools

  ✅ 👥 Section 2: Specialist Content Agents

  Each request gets routed to one (or several) of these agents, depending on the strategy.

  3️⃣ Blog Content Writer

  Long-form articles, editorials, and thought leadership pieces.

  4️⃣ Social Media Content Creator

  Social posts, captions, hashtags, and community content.

  5️⃣ Video Script Writer

  YouTube scripts, explainer videos, and video marketing content.

  6️⃣ Email Newsletter Writer

  Campaigns, nurture sequences, and newsletter copy.

  7️⃣ Website Copy Specialist

  Landing pages, product descriptions, and conversion-focused web copy.

  8️⃣ Content Strategist & Planner
  Editorial calendars, campaign planning, and audience strategy.

  💡 Beginner Benefit

  ✅ Each agent is an expert in its field
  ✅ Powered by GPT-4.1-mini → faster and cheaper
  ✅ Parallel execution → all content types can be generated at once

  ✅ 🧠 Section 3: Language Models & Execution Flow

  O3 Model → Content Director**

    Handles analysis, strategy, and delegation.

  GPT-4.1-mini → All Specialists**

    Powers blog, social, video, email, website, and strategy agents.

  Think Node**

    Helps the Content Director organize reasoning before delegating tasks.

  💡 Beginner Benefit

  ✅ AI Director (O3) = smart leadership
  ✅ Specialists (GPT-4.1-mini) = cost-efficient execution
  ✅ Built-in reasoning = better, more aligned campaigns

  📊 Workflow Overview

  | Section                     | What Happens                                                    | Key Benefit                |
  | --------------------------- | --------------------------------------------------------------- | -------------------------- |
  | 📩 Trigger & Director Setup | Workflow starts from chat → Content Director interprets request | Centralized control        |
  | 👥 Specialist Agents        | Each AI agent produces tailored content                         | Multi-channel coverage     |
  | 🧠 Models & Flow            | O3 for Director, GPT-4.1-mini for specialists                   | Cost-efficient + strategic |

  📌 How You Benefit Overall

  ✅ One input → full content campaign
  ✅ Consistent brand voice across all platforms
  ✅ Cost-effective (O3 only for strategy, GPT-4.1-mini for bulk work)
  ✅ Ready-to-publish content in minutes

  ✨ You’ve basically built an AI marketing department inside n8n — no extra staff required! 🚀

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name: Creative Design Agency Simulation with OpenAI O3 and GPT-4.1-mini Multi-Agent
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:03:54.373Z
updated_at: 2025-08-02T18:03:54.373Z
url: https://n8n.io/workflows/6914
scraped_at: 2025-12-24 13:02:42
description:
  Creative Design Agency Simulation with OpenAI O3 and GPT-4.1-mini Multi-Agent Team

  This n8n workflow simulates a full-service creative agency powered by AI. At the center is a Creative Director Agent (O3 model) who takes client requests, plans the creative direction, and delegates work to a specialized design team. Each specialist runs on GPT-4.1-mini, keeping execution fast and cost-efficient.

  🟢 Section 1 – Entry & Strategic Leadership

  Nodes:

  💬 When chat message received → Entry point, listens for design briefs.
  🎨 Creative Director Agent (O3) → The “agency head” who interprets requirements and decides which specialists to involve.
  💡 Think Tool → Helps the Director brainstorm, evaluate alternatives, and refine direction.
  🧠 OpenAI Chat Model Director (O3) → Strategic reasoning engine for the Director.

  ✅ Benefit for beginners: Think of this as the project manager’s desk — you submit a design request, and the Director figures out how to make it happen.

  ✍️ Section 2 – Core Creative Specialists

  Nodes:

  🖼️ Graphic Designer → Logos, visual identity, print, packaging.
  📱 UI/UX Designer → Wireframes, prototypes, interaction design.
  🎯 Brand Strategist → Market positioning, brand guidelines, competitive research.
  📝 Creative Copywriter → Taglines, messaging, campaign copy.

  Each agent is powered by GPT-4.1-mini.

  ✅ Benefit for beginners: This section is your creative studio team — they craft visuals, design user experiences, and write compelling words.

  🚀 Section 3 – Extended Design & Motion Team

  Nodes:

  🎬 Motion Graphics Designer → Animations, promo videos, explainer graphics.
  🌐 Web Designer → Websites, responsive layouts, accessibility improvements.
  🖌️ OpenAI Chat Model Agents (GPT-4.1-mini) → Back each specialist with creative power.

  ✅ Benefit for beginners: This section brings motion and web into the mix, ensuring your creative package isn’t static — it moves, animates, and lives online.

  📊 Summary Table

  | Section             | Key Roles                         | Model        | Purpose               | Beginner Benefit                      |
  | ------------------- | --------------------------------- | ------------ | --------------------- | ------------------------------------- |
  | 🟢 Entry & Strategy | Chat Trigger, Director, Think     | O3           | Leadership & planning | Turns briefs into action plans        |
  | ✍️ Core Creatives   | Graphic, UI/UX, Brand, Copywriter | GPT-4.1-mini | Design & content      | Produces visuals, UX, and words       |
  | 🚀 Extended Team    | Motion Graphics, Web              | GPT-4.1-mini | Motion & web design   | Animates, builds, and scales projects |

  🌟 Why This Workflow Rocks

  Complete agency in a box** → Strategy + Design + Motion + Web + Copy
  Smart leadership** → Director (O3) only used for high-level thinking
  Cost-effective execution** → GPT-4.1-mini runs most tasks
  Parallel creativity** → Specialists work simultaneously
  Scalable** → Adaptable to any design or branding request

  👉 Example: Send a message like “Design a brand identity for a sustainable clothing startup”.
  Within minutes, your AI agency produces:

  A logo & color scheme 🎨
  A UX prototype 📱
  A brand positioning doc 🎯
  Animated ad ideas 🎬
  Website mockups 🌐
  A tagline & ad copy ✍️

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name: Amplify Social Media Presence with O3 and GPT-4 Multi-Agent Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:04:18.274Z
updated_at: 2025-08-02T18:04:18.274Z
url: https://n8n.io/workflows/6915
scraped_at: 2025-12-24 13:02:44
description:
  Amplify Social Media Presence with O3 and GPT-4 Multi-Agent Team

  🌍 Overview

  This n8n workflow acts like a virtual social media department. A Social Media Director Agent coordinates multiple specialized AI agents (Instagram, Twitter/X, Facebook, TikTok, YouTube, and Analytics). Each agent creates or analyzes content for its platform, powered by OpenAI models.

  The result? A fully automated, cross-platform social media strategy—from content creation to performance tracking.

  🟢 Section 1: Trigger & Director Setup

  🔗 Nodes:

  When chat message received (Trigger)** → Starts the workflow whenever you send a request (e.g., “Plan a TikTok campaign for my product launch”).
  Social Media Director Agent* (connected to *OpenAI O3 model**) → Acts as the strategist.
  Think Tool** → Helps the Director “reason” before delegating.

  💡 Beginner takeaway:
  This section makes your workflow interactive. You send a request → the Director decides the best approach → then it assigns tasks.

  📈 Advantage:
  Instead of manually planning content per platform, you only send one command, and the AI Director handles the strategy.

  🟦 Section 2: Specialized Social Media Agents

  🔗 Nodes (each paired with GPT-4.1-mini):

  📸 Instagram Content Creator → Visual storytelling, Reels, Hashtags
  🐦 Twitter/X Strategist → Viral tweets, trends, engagement
  👥 Facebook Community Manager → Audience growth, ads, group engagement
  🎵 TikTok Video Creator → Short-form video, viral trends
  🎬 YouTube Content Planner → Long-form strategy, SEO, thumbnails
  📊 Analytics Specialist → Performance insights, cross-platform reporting

  💡 Beginner takeaway:
  Each platform has its own AI expert. They receive the Director’s strategy and produce tailored content for their platform.

  📈 Advantage:
  Instead of one-size-fits-all posts, you get optimized content per platform—increasing reach and engagement.

  🟣 Section 3: Models & Connections

  🔗 Nodes:

  OpenAI Chat Models** (O3 + multiple GPT-4.1-mini models)
  Each model is connected to its respective agent.

  💡 Beginner takeaway:
  Think of these as the “brains” behind each specialist. The Director uses O3 for advanced reasoning, while the specialists use GPT-4.1-mini (cheaper, faster) for content generation.

  📈 Advantage:
  This keeps costs low while maintaining quality output.

  📊 Final Overview Table

  | Section               | Nodes                                                    | Purpose                                | Benefit                        |
  | --------------------- | -------------------------------------------------------- | -------------------------------------- | ------------------------------ |
  | 🟢 Trigger & Director | Chat Trigger, Director, Think Tool                       | Capture requests & plan strategy       | One command → full social plan |
  | 🟦 Specialists        | Instagram, Twitter, Facebook, TikTok, YouTube, Analytics | Platform-specific content              | Optimized posts per platform   |
  | 🟣 Models             | O3 + GPT-4.1-mini                                        | Provide reasoning & content generation | High-quality, cost-efficient   |

  🚀 Why This Workflow is Powerful

  Multi-platform coverage**: All major platforms handled in one flow
  Human-like strategy**: Director agent makes real marketing decisions
  Scalable & fast**: Generate a full campaign in minutes
  Cost-effective**: O3 only for strategy, GPT-4.1-mini for bulk content
  Beginner-friendly**: Just type your request → get full campaign output

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name: Create Viral LinkedIn Content with O3 & GPT-4.1-mini Multi-Agent Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:04:42.673Z
updated_at: 2025-08-02T18:04:42.673Z
url: https://n8n.io/workflows/6916
scraped_at: 2025-12-24 13:02:43
description:
  Create Viral LinkedIn Content with O3 & GPT-4.1-mini Multi-Agent Team

  This n8n workflow is a multi-agent LinkedIn content factory.
  At its heart is the Content Director Agent (O3 model), who acts as the project manager. It listens for LinkedIn chat messages, analyzes them, and coordinates a team of AI specialists (all powered by GPT-4.1-mini) to produce viral, engaging, and optimized LinkedIn content.

  🟢 Section 1 – Workflow Entry & Strategy Layer

  Nodes:

  🔔 When chat message received → Captures LinkedIn requests (your idea, draft, or prompt).
  🧠 Content Director Agent (O3) → Acts as the leader, deciding how the content should be structured and which specialists to call.
  💡 Think Node → Helps the Director brainstorm and evaluate possible approaches before delegating.
  🤖 OpenAI Chat Model Director (O3) → The Director’s brain, providing strategic-level thinking.

  ✅ Beginner-friendly benefit: This section is like the “command center.” Any LinkedIn content request starts here and gets transformed into a clear, strategic plan before moving to specialists.

  ✍️ Section 2 – Content Creation Specialists

  Nodes:

  ✍️ LinkedIn Copywriter → Creates viral hooks, compelling posts, and platform-friendly messaging.
  🎓 Domain Expert → Ensures technical accuracy and industry authority in the post.
  📝 Proofreader & Editor → Polishes content for grammar, tone, and style.

  Each agent connects to its own GPT-4.1-mini model for cost-efficient, specialized output.

  ✅ Beginner-friendly benefit: This section is like your content writing team—from drafting, to adding expertise, to polishing for professional LinkedIn standards.

  🚀 Section 3 – Engagement & Optimization Specialists

  Nodes:

  🚀 Engagement Strategist → Crafts hashtags, posting times, and audience growth strategies.
  🎨 Visual Content Strategist → Designs carousels, infographics, and visual ideas.
  📊 Content Performance Analyst → Tracks analytics, measures performance, and suggests improvements.

  Each of these also relies on GPT-4.1-mini, keeping cost low while delivering specialized insights.

  ✅ Beginner-friendly benefit: This section is like your growth & marketing team—they ensure your content doesn’t just look good but also performs well and reaches the right audience.

  📊 Summary Table

  | Section                      | Key Nodes                              | Role                 | Beginner Benefit                        |
  | ---------------------------- | -------------------------------------- | -------------------- | --------------------------------------- |
  | 🟢 Entry & Strategy          | Trigger, Director, Think, O3 Model     | Strategy & planning  | Turns your idea into a clear strategy   |
  | ✍️ Content Creation          | Copywriter, Domain Expert, Proofreader | Writing & refinement | Produces expert-level, polished content |
  | 🚀 Engagement & Optimization | Engagement, Visuals, Analytics         | Growth & performance | Maximizes reach, visuals, and results   |

  🌟 Why This Workflow Rocks

  All-in-one content team** → Strategy + Writing + Optimization
  Low cost** → O3 only for strategy, GPT-4.1-mini for specialists
  Parallel agents** → Work simultaneously for faster results
  Scalable** → Reusable for any LinkedIn content need

  👉 Even a beginner can use this workflow: just send a LinkedIn content idea (e.g., “Write a post on AI in finance”), and your AI team handles the rest—writing, polishing, visuals, and engagement tactics.

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name: Automate Vendor Contract Renewals & Reminders with GPT-4.1 mini, Slack & Gmail
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-03T13:24:37.325Z
updated_at: 2025-08-03T13:24:37.325Z
url: https://n8n.io/workflows/6935
scraped_at: 2025-12-24 13:02:45
description:
  📝 Smart Vendor Contract Renewal & Reminder Workflow With GPT 4.1 mini
  Watch the demo video below:

  Never miss a vendor renewal again!
  This smart workflow automatically tracks expiring contracts, reminds your finance team via Slack, and helps initiate renewal with vendors through email — all with built-in approval and logging. Perfect for managing both auto-renew and manual contracts.
  📌 Who’s it for
  This workflow is designed for Finance and Procurement teams responsible for managing vendor/service contracts. It ensures timely notifications for expiring contracts and automates the initiation of renewal conversations with vendors.

  ⚙️ How it works / What it does

  ⏰ Daily Trigger
     Runs every day at 6:00 AM using a scheduler.

  📄 Retrieve Contract List
     Reads vendor contract data from a Google Sheet (or any data source).
     Filters for contracts nearing their end date, using a Notice Period (days) field.

  🔀 Branch Based on Renewal Type
     Auto-Renew Contracts:
       Compose a Slack message summarizing the auto-renewal.
       Notify the finance contact via Slack.

     Manual Renewal Contracts:
       Use an OpenAI-powered agent to generate a meaningful Slack message.
       Send message and wait for approval from the finance contact (e.g., within 8 hours).
       Upon approval, generate a formal HTML email to the vendor.
       Send the email to initiate the contract extension process.

  📊 (Optional) Logging
     Can be extended to log all actions (Slack messages, emails, approvals) to Google Sheets or other databases.

  🛠️ How to set up

  Prepare your Google Sheet
     Include the following fields:
       Vendor Name, Vendor Email, Service Type, Contract Start Date, Contract End Date, Notice Period (days), Renewal Type, Finance Contact, Contact Email, Slack ID, Contract Value, Notes.
       Sample: https://docs.google.com/spreadsheets/d/1zdDgKyL0sY54By57Yz4dNokQC_oIbVxcCKeWJ6PADBM/edit?usp=sharing

  Configure Integrations
     🟢 Google Sheets API: To read contract data.
     🔵 Slack API: To notify and wait for approval.
     🧠 OpenAI API (GPT-4): To generate personalized reminders.
     ✉️ Email (SMTP/Gmail): To send emails to vendors.

  Set the Daily Scheduler
     Use a Cron node to trigger the workflow at 6:00 AM daily.

  ✅ Requirements

  | Component                        | Required |
  |----------------------------------|----------|
  | Google Sheets API                | ✅       |
  | Slack API                        | ✅       |
  | OpenAI API (GPT-4)               | ✅       |
  | Email (SMTP/Gmail)               | ✅       |
  | n8n (Self-hosted or Cloud)       | ✅       |
  | Contract Sheet with proper schema| ✅       |

  🧩 How to customize the workflow
  Adjust Reminder Period**: Modify the logic in the Find Expiring Vendors node (based on Contract End Date and Notice Period).
  Change Message Tone or Format**: Customize the OpenAI agent's prompt or switch from plain text to branded HTML email.
  Add Logging or Tracking: Add a node to append logs to a **Google Sheet, Notion, or database.
  Replace Data Source: Swap out Google Sheets for **Airtable, PostgreSQL, or other CRM/database systems.
  Adjust Wait/Approval Duration**: Modify the sendAndWait Slack node timeout (e.g., from 8 hours to 2 hours).

  📦 Optional Extensions
  🧾 Add PDF contract preview via Drive link
  🧠 Use GPT to summarize renewal terms
  🛠 Auto-create Jira task for contract review

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name: Automatically Save & Organize Outlook Email Attachments in OneDrive Folders
author_name: Michael Gullo
author_username: mgullo
categories: []
created_at: 2025-08-03T16:05:57.477Z
updated_at: 2025-08-03T16:05:57.477Z
url: https://n8n.io/workflows/6938
scraped_at: 2025-12-24 13:02:41
description:
  Outlook to OneDrive
  This workflow automates the process of saving binary attachments from Outlook emails into newly created folders in OneDrive. It's ideal for users who regularly receive files and need them organized into separate folders without manual intervention. Each folder is automatically named based on the email subject and the current timestamp, allowing all attachments from that email to be stored inside the corresponding folder. This is particularly useful for streamlining document workflows, improving file traceability, and reducing the time spent on repetitive tasks like organizing client submissions, invoices, or internal reports.

  The configuration and setup of the workflow can be customized to meet the business or personal needs of the user. Its purpose is to automatically process binary attachments from Outlook emails and upload them to dynamically created folders in OneDrive.

  Overview
  Microsoft Outlook Trigger – Monitors your inbox for new emails.
  Filter – Ensures only emails with binary attachments proceed.
  Get Outlook Message – Retrieves the full email and downloads attachments.
  Create Folder – Makes a new folder in OneDrive based on the email subject and time.
  Split Out – Extracts each binary attachment.
  Merge– Combines folder and file data before upload.
  Upload File OneDrive – Uploads each binary file into the new folder.

  Need Help? Have Questions?
  For consulting and support, or if you have questions, please feel free to connect with me on LinkedIn or via email. 

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name: Enhance Your Workflow with 2Ndmoises_Generator AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-03T17:02:44.280Z
updated_at: 2025-08-03T17:02:44.280Z
url: https://n8n.io/workflows/6943
scraped_at: 2025-12-24 13:02:45
description:
  Enhance Your Workflow with 2Ndmoises_Generator AI

  This n8n workflow integrates with Replicate’s moicarmonas/2ndmoises_generator model to generate custom outputs based on your prompt. It handles authentication, triggers the prediction, monitors progress, and processes the final result automatically.

  📌 Section 1: Trigger & Authentication

  ⚡ On Clicking ‘Execute’ (Manual Trigger)

  Purpose: Start the workflow manually whenever you want to run it.
  Benefit: Great for testing or running on-demand without needing automation.

  🔑 Set API Key (Set Node)

  Purpose: Stores your Replicate API key in the workflow.
  How it works: Adds your API key as a variable that other nodes can reference.
  Benefit: Keeps credentials secure and reusable.

  📌 Section 2: Sending the AI Request

  📤 Create Prediction (HTTP Request Node)

  Purpose: Sends a request to the Replicate API to start generating output with the model.
  Input Parameters:

    prompt (text you provide)
    seed (for reproducibility)
    width / height / lora\_scale (generation settings)
  Benefit: Allows full customization of the AI’s generation process.

  🆔 Extract Prediction ID (Code Node)

  Purpose: Pulls out the Prediction ID and status from the API response.
  Why important: The ID is required to check the job’s progress later.
  Benefit: Automates polling without manual tracking.

  📌 Section 3: Polling & Waiting

  ⏳ Wait (Wait Node)

  Purpose: Adds a short pause (2 seconds) between checks.
  Benefit: Prevents hitting the API too quickly and avoids errors.

  🔄 Check Prediction Status (HTTP Request Node)

  Purpose: Calls Replicate again to ask if the prediction is finished.
  Benefit: Automates progress monitoring without manual refresh.

  ✅ Check If Complete (If Node)

  Purpose: Decides whether the model has finished generating.
  Paths:

    True → Move on to processing the result.
    False → Go back to Wait and recheck.
  Benefit: Ensures the workflow loops until a final output is ready.

  📌 Section 4: Handling the Result

  📦 Process Result (Code Node)

  Purpose: Cleans up the final API response and extracts:

    Status
    Output (generated result)
    Metrics
    Timestamps (created\_at / completed\_at)
    Model info
  Benefit: Provides a structured, ready-to-use output for other workflows or integrations.

  📊 Workflow Overview Table

  | Section           | Node Name               | Purpose                      |
  | ----------------- | ----------------------- | ---------------------------- |
  | 1. Trigger & Auth | On Clicking ‘Execute’   | Starts the workflow manually |
  |                   | Set API Key             | Stores API credentials       |
  | 2. AI Request     | Create Prediction       | Sends request to Replicate   |
  |                   | Extract Prediction ID   | Gets prediction ID + status  |
  | 3. Polling        | Wait                    | Adds delay before recheck    |
  |                   | Check Prediction Status | Monitors progress            |
  |                   | Check If Complete       | Routes based on completion   |
  | 4. Result         | Process Result          | Extracts and cleans output   |
  | Notes             | Sticky Note             | Explains setup + model info  |

  🎯 Key Benefits

  🔐 Secure authentication using Set node for API key storage.
  🤖 Hands-free generation — just provide a prompt, the workflow handles everything else.
  🔄 Automated polling ensures you always get the final result without manual checking.
  📦 Clean structured output ready for downstream use in apps, dashboards, or notifications.

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name: Scan URLs with urlscan.io and Send Results via Gmail
author_name: Calistus Christian
author_username: ca7ai
categories: []
created_at: 2025-08-03T17:33:19.945Z
updated_at: 2025-08-03T17:33:19.945Z
url: https://n8n.io/workflows/6946
scraped_at: 2025-12-24 13:02:46
description:
  Overview
  Receive a URL via Webhook, submit it to urlscan.io, wait ~30 seconds for artifacts (e.g., screenshot), then email a clean summary with links to the result page, screenshot, and API JSON.

  What this template does
  Ingests a URL from a POST request.
  Submits the URL to urlscan.io and captures the scan UUID.
  Waits 30s** to give urlscan time to generate the screenshot and result artifacts.
  Sends a formatted HTML email via Gmail with all relevant links.

  Nodes used
  Webhook** (POST /urlscan)
  urlscan.io → Perform a scan**
  Wait** (30 seconds; configurable)
  Gmail → Send a message**

  Input
  { "url": "https://example.com" }

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name: Backup n8n Workflows with Versioning and Notion Tracking
author_name: Stéphane Heckel
author_username: stephaneheckel
categories: []
created_at: 2025-08-03T17:52:26.644Z
updated_at: 2025-08-03T17:52:26.644Z
url: https://n8n.io/workflows/6947
scraped_at: 2025-12-24 13:02:44
description:
  Copy n8n workflows to a slave n8n repository

  Inspired by Alex Kim's workflow, this version adds the ability to keep multiple versions of the same workflow on the destination instance. Each copied workflow’s name is prefixed with the date (YYYY_MM_DD_), enabling simple version tracking. Process details and workflow counts are recorded centrally in Notion.

  How it works

  Workflows from the source n8n instance are copied to the destination using the n8n API node.
  On the destination, each workflow name is prefixed with the current date (e.g., 2025_08_03_PDF Summarizer), so you can keep multiple daily versions.
  The workflow tracks and saves:
      The date of execution.
      Number of workflows processed.
      Both details are recorded in Notion.

  Rolling retention policy example:

  Day 1:** Workflows are saved with 2025_08_03_ prefix.
  Day 2:** New set saved with 2025_08_04_.
  Day 3:** Day 1’s set is deleted, new set saved as 2025_08_05_.
  To keep more days, adjust the “Subtract From Date” node.

  How to use

  Create a Notion database with one page and three fields:
      sequence: Should contain "prefix".
      Value: Today's date as YYYY_MM_DD_.
      Comment: Number of saved workflows.

  Configure the Notion node:
      Enter your Notion credentials.
      Link to the created database/page.

  Update the "Subtract From Date" node:
      Set how many days’ versions you want to keep (default: 2 days).
      Set the limit to 1 in the "Limit" node for testing.
  Input credentials for both source and destination n8n instances.

  Requirements

  Notion** for tracking execution date and workflow count.
  n8n API Keys* for both source and destination instances. Ensure you have the necessary *API permissions** (read, create, delete workflows)
  n8n version** this workflow was tested on 1.103.2 (Ubuntu)

  Need Help?

  Comment this post or contact me on LinkedIn
  Ask in the Forum!

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name: Daily Calendar Summary Notifications via Telegram from Google Calendar
author_name: Yassin Zehar
author_username: yassinzehar
categories: []
created_at: 2025-08-03T18:33:22.621Z
updated_at: 2025-08-03T18:33:22.621Z
url: https://n8n.io/workflows/6952
scraped_at: 2025-12-24 13:02:45
description:
  Context:
  This workflow automatically sends you a daily message on Telegram summarizing all your meetings and events for the day, straight from your Google Calendar.

  For who ? 
  Perfect for anyone who:
  Uses Google Calendar to manage their schedule.
  Wants Telegram reminders for daily events.
  Loves automation and productivity tools.

  Requirements:
  Telegram.
  Google account.
  Google Calendar.

  Steps:


  🗒️ Use the sticky notes in the n8n canvas to:
  Add your Telegram and Google credentials.
  Execute and test the workflow.
  Check if you receive your daily summary on Telegram.

  You'll get this:

  Tutorial video:
  Watch the Youtube Tutorial video

  How does it work?
  ⏰ The trigger runs every day at 7AM.
  📅 Your Google Calendar is checked.
  🔢 If there are events or meetings, a number &gt; 0 is returned. Otherwise, it's 0.
  📝 A text message is generated with a summary of all your events, including all relevant details.
  ❌ If no events are found, a "no event" message is sent.

  About me :
  I’m Yassin a Project & Product Manager  Scaling tech products with data-driven project management.
  📬 Feel free to connect with me on Linkedin

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name: Automate Your Magento 2 Weekly Sales & Performance Reports
author_name: Kanaka Kishore Kandregula
author_username: kmyprojects
categories: []
created_at: 2025-08-03T22:56:21.791Z
updated_at: 2025-08-03T22:56:21.791Z
url: https://n8n.io/workflows/6953
scraped_at: 2025-12-24 13:02:45
description:
  Automatically fetches last week’s Magento 2 orders, summarises sales and product performance, logs the data to Google Sheets, and emails a polished report — all without logging into admin or buying extra modules. 

  Perfect for store owners and agencies.

  ✅ What This Workflow Does:
  This workflow automatically fetches the last 7 days of orders from your Magento 2 store, summarizes key metrics (orders, revenue, products sold), groups product performance data, generates a Google Sheet with two tabs (Weekly Summary & Product Breakdown), and emails the report to your team in a modern dashboard-style HTML format — all without ever logging into Magento admin.

  🔧 Modules Used:
  🕒 Schedule Trigger
  ⚙️ Code (JavaScript)
  🌐 HTTP Request
  📊 Google Sheets
  ✉️ Gmail (HTML Email with custom design)

  💼 Use Cases:
  E-commerce store managers who want weekly sales snapshots without logging into Magento 2.
  Agencies managing multiple Magento clients and reporting to them weekly.
  Business owners who want automated insights without paying for extra reporting modules.
  Marketing or growth teams that need product-wise performance regularly in Google Sheets.

  🔒 Credentials Required:
  Magento 2 API (Bearer Token)
  Google Sheets OAuth2
  Gmail OAuth2 (for sending HTML email reports)

  📂 Category:
  E-commerce / Magento 2 / Reporting / Automation

  ✨ Why This Saves Hours:
  This workflow replaces manual Magento report exports, repetitive data cleanup, and weekly email formatting. Store managers often waste 1–2 hours/week collecting data — now it takes 0 minutes. Just set it and forget it.
  You don’t need to buy reporting extensions, log into the admin, or manually touch a spreadsheet again.

  🤝 Need a Custom Workflow?
  If you need this tailored for your own workflow, store, or client —
  📩 Let’s connect. I build custom, high-performance n8n automations for e-commerce, growth, and reporting.

  Contact: Author

  👤 Author
  Kanaka Kishore Kandregula
  Certified Magento 2 Developer
  https://gravatar.com/kmyprojects
  https://www.linkedin.com/in/kanakakishore

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name: Generate Videos from Images with Wan 2.2 I2V A14B AI Model
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-04T14:24:22.279Z
updated_at: 2025-08-04T14:24:22.279Z
url: https://n8n.io/workflows/6966
scraped_at: 2025-12-24 13:02:43
description:
  Generate Videos from Images with Wan 2.2 I2V A14B AI Model

  🌍 Overview

  This workflow connects n8n with Replicate’s Wan-Video model to generate video content from an image + prompt.
  It handles:

  🔑 API authentication
  📤 Sending a generation request
  ⏳ Polling until completion
  📥 Returning a downloadable video link

  🟢 Section 1: Start & Authentication

  🔗 Nodes:
  1️⃣ On clicking 'execute' (Manual Trigger)
  ▶️ Starts the workflow manually when you click Execute Workflow.

  2️⃣ Set API Key
  🔑 Stores your Replicate API Key securely inside n8n.

  Value: YOUR_REPLICATE_API_KEY

  💡 Beginner Benefit:
  ✅ No need to hardcode API keys in every request
  ✅ Easy to swap keys for different accounts

  🔵 Section 2: Send Video Generation Request

  🔗 Nodes:
  3️⃣ Create Prediction (HTTP Request)
  📤 Sends a request to Replicate API → /v1/predictions

  Model: wan-video/wan-2.2-i2v-a14b
  Input Parameters:

    📝 prompt → your text description
    🖼️ image → input video/image URL
    🎲 seed → reproducibility
    🎞️ num_frames → 81 frames
    ⏩ sample_shift → 5
    ⚙️ sample_steps → 30
    🎬 frames_per_second → 16

  4️⃣ Extract Prediction ID (Code)
  🆔 Pulls out the prediction ID + status from Replicate’s response.
  This ID is needed for polling until the video finishes generating.

  💡 Beginner Benefit:
  ✅ Automates the API call to generate video
  ✅ Extracts ID → avoids manual copy-paste

  🟣 Section 3: Polling & Status Check

  🔗 Nodes:
  5️⃣ Wait (2 sec)
  ⏳ Adds a short delay before checking progress.

  Prevents API spam

  6️⃣ Check Prediction Status (HTTP Request)
  🔄 Calls Replicate API → /v1/predictions/{id}

  Checks whether the video is still processing or finished

  7️⃣ Check If Complete (IF Node)
  ❓ Compares status → succeeded or not

  ✅ If complete → goes to Process Result
  ❌ If not → loops back to Wait and tries again

  💡 Beginner Benefit:
  ✅ Automatic re-checking → you don’t need to refresh manually
  ✅ Works until result is ready

  🟡 Section 4: Process Final Result

  🔗 Nodes:
  8️⃣ Process Result (Code)
  📥 Once complete, extracts:

  ✅ Status
  🎞️ Output video URL
  📊 Generation metrics
  ⏱️ Timestamps (created\_at, completed\_at)
  🧩 Model used

  Final output = direct video URL you can download/share 🎥

  📊 Final Overview

  | Section   | What Happens                   | Why It’s Useful                   |
  | --------- | ------------------------------ | --------------------------------- |
  | 🟢 Auth   | Manual Trigger + API Key       | Secure, easy start                |
  | 🔵 Send   | Create Prediction + Extract ID | Kicks off video generation        |
  | 🟣 Poll   | Wait + Check Status + IF       | Auto-checks progress until done   |
  | 🟡 Result | Process Result                 | Gives final video link + metadata |

  🚀 Why This Workflow Rocks

  🎥 Video from Image + Prompt → AI-powered video generation in minutes
  🔄 Fully automated → from request to final video, no manual checks
  🔑 Secure → API keys handled safely
  ⚙️ Customizable → tweak frames, FPS, prompt, seed

  ✨ With this workflow, you’ve got a personal AI video generator inside n8n — all you need to do is provide a prompt + input image/video, and you’ll get a fresh AI video link back.

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name: Generate Custom Text Content with IBM Granite 3.3 8B Instruct AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-04T14:25:22.747Z
updated_at: 2025-08-04T14:25:22.747Z
url: https://n8n.io/workflows/6968
scraped_at: 2025-12-24 13:02:46
description:
  Generate Custom Text Content with IBM Granite 3.3 8B Instruct AI

  This workflow connects to Replicate’s API and uses the ibm-granite/granite-3.3-8b-instruct model to generate text.

  ✅ 🔵 SECTION 1: Trigger & Setup

  ⚙️ Nodes

  1️⃣ On clicking 'execute'

  What it does:* Starts the workflow manually when you hit *Execute.
  Why it’s useful:** Perfect for testing text generation on-demand.

  2️⃣ Set API Key

  What it does:* Stores your *Replicate API key** securely.
  Why it’s useful:** You don’t hardcode credentials into HTTP nodes — just set them once here.
  Beginner tip:** Replace YOUR_REPLICATE_API_KEY with your actual API key.

  💡 Beginner Benefit

  ✅ No coding needed to handle authentication.
  ✅ You can reuse the same setup for other Replicate models.

  ✅ 🤖 SECTION 2: Model Request & Polling

  ⚙️ Nodes

  3️⃣ Create Prediction (HTTP Request)

  What it does:* Sends a *POST request** to Replicate’s API to start a text generation job.
  Parameters include:** temperature, max_tokens, top_k, top_p.
  Why it’s useful:** Controls how creative or focused the AI text output will be.

  4️⃣ Extract Prediction ID (Code)

  What it does:* Pulls the *prediction ID** and builds a URL for checking status.
  Why it’s useful:** Replicate jobs run asynchronously, so you need the ID to track progress.

  5️⃣ Wait

  What it does:* Pauses for *2 seconds** before checking the prediction again.
  Why it’s useful:** Prevents spamming the API with too many requests.

  6️⃣ Check Prediction Status (HTTP Request)

  What it does:* Polls the Replicate API for the *current status** (e.g., starting, processing, succeeded).
  Why it’s useful:** Lets you loop until the AI finishes generating text.

  7️⃣ Check If Complete (IF Condition)

  What it does:* If the status is *succeeded, it goes to “Process Result.” Otherwise, it loops back to **Wait and retries.
  Why it’s useful:** Creates an automated polling loop without writing complex code.

  💡 Beginner Benefit

  ✅ No need to manually refresh or check job status.
  ✅ Workflow keeps retrying until text is ready.
  ✅ Smart looping built-in with Wait + If Condition.

  ✅ 🟢 SECTION 3: Process & Output

  ⚙️ Nodes

  8️⃣ Process Result (Code)

  What it does:* Collects the final *AI output**, status, metrics, and timestamps.
  Adds info like:**

    ✅ output → Generated text
    ✅ model → ibm-granite/granite-3.3-8b-instruct
    ✅ metrics → Performance data
  Why it’s useful:** Gives you a neat, structured JSON result that’s easy to send to Sheets, Notion, or any app.

  💡 Beginner Benefit

  ✅ Ready-to-use text output.
  ✅ Easy integration with any database or CRM.
  ✅ Transparent metrics (when it started, when it finished, etc.).

  ✅✅✅ ✨ FULL FLOW OVERVIEW

  | Section                        | What happens                                                                 |
  | ------------------------------ | ---------------------------------------------------------------------------- |
  | ⚡ Trigger & Setup          | Start workflow + set Replicate API key.                                      |
  | 🤖 Model Request & Polling | Send request → get Prediction ID → loop until job completes.                 |
  | 🟢 Process & Output        | Extract clean AI-generated text + metadata for storage or further workflows. |

  📌 How You Benefit Overall

  ✅ No coding needed — just configure your API key.
  ✅ Reliable polling — the workflow waits until results are ready.
  ✅ Flexible — you can extend output to Google Sheets, Slack, Notion, or email.
  ✅ Beginner-friendly — clean separation of input, process, and output.

  ✨ With this workflow, you’ve turned Replicate’s IBM Granite LLM into a no-code text generator — running entirely inside n8n! ✨

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.code","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, 5044 characters]


name: Track Expenses from Telegram to Google Sheets with GPT-4.1 Mini
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-04T14:53:50.938Z
updated_at: 2025-08-04T14:53:50.938Z
url: https://n8n.io/workflows/6970
scraped_at: 2025-12-24 13:02:43
description:
  📒 Telegram Expense Tracker to Google Sheets with GPT-4.1
  .jpg)
  &gt; A lightweight automation that lets users log daily expenses via a Telegram bot and instantly saves them into Google Sheets—perfect for anyone looking to manage spending on the go with AI-powered structure and ease.
  👤 Who’s it for
  This workflow is for anyone who wants to log their daily expenses by simply chatting with a Telegram bot. Ideal for:
  Individuals who want a quick way to track spending
  Freelancers who log receipts and purchases on the go
  Teams or small business owners who want lightweight expense capture

  ⚙️ How it works / What it does
  User sends a text message on Telegram describing an expense  
     (e.g., “Bought coffee for 50k at Highlands”)

  Message format is validated
     If the message is text, it proceeds to GPT-4.1 Mini for processing.
     If it's not text (e.g. image or file), the bot sends a fallback message.

  OpenAI GPT-4.1 Mini parses the message and returns:
     relevant: true/false
     expense_record: structured fields (date, amount, currency, category, description, source)
     message: a friendly confirmation or fallback

  If valid:
     The bot replies with a fun acknowledgment
     The data is saved to a connected Google Sheet

  If invalid:
     A fallback message is sent to encourage proper input

  🛠️ How to set up

  1. Telegram Bot Setup
  Create a bot using BotFather on Telegram
  Copy the bot token and paste it into the Telegram Trigger node

  2. Google Sheet Setup
  Create a Google Sheet with these columns:
      Date | Amount | Currency | Category | Description | SourceMessage
    Share the sheet with your n8n service account email

  3. OpenAI Configuration
  Connect the OpenAI Chat Model node using your OpenAI API key
  Use GPT-4.1 Mini as the model
  Apply a system prompt that extracts structured JSON with:
    relevant, expense_record, and message

  4. Add Parser
  Use the Structured Output Parser node to safely parse the JSON response

  5. Conditional Logic Nodes
  Is text message?  
     Checks if the message is in text format  
  Supported scenario?  
     Checks if relevant = true in the LLM response

  6. Final Actions
  If relevant**:  
     Send confirmation via Telegram  
     Append row to Google Sheet  
  If not relevant**:  
     Send fallback message via Telegram

  ✅ Requirements
  Telegram bot token
  OpenAI GPT-4.1 Mini API access
  n8n instance (self-hosted or cloud)
  Google Sheet with access granted to n8n
  Basic understanding of n8n node configuration

  🧩 How to customize the workflow

  | Feature                         | How to Customize                                                  |
  |----------------------------------|-------------------------------------------------------------------|
  | Add multi-currency support       | Update system prompt to detect and extract different currencies  |
  | Add more categories              | Modify the list of categories in the system prompt               |
  | Track multiple users             | Add username or chat ID column to the Google Sheet           |
  | Trigger alerts                   | Add Slack, Email, or Telegram alerts for specific expense types  |
  | Weekly summaries                 | Use a cron node + Google Sheet query + Telegram message          |
  | Visual dashboards                | Connect the sheet to Looker Studio or Google Data Studio         |

  Built with 💬 Telegram + 🧠 GPT-4.1 Mini + 📊 Google Sheets + ⚡ n8n

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.if","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","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Website Contact Form to Slack with Optional Email Confirmation
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-04T23:17:08.377Z
updated_at: 2025-08-04T23:17:08.377Z
url: https://n8n.io/workflows/6987
scraped_at: 2025-12-24 13:02:45
description:
  This n8n workflow sends a real-time Slack notification when a user submits a contact form on your website. It also optionally sends a confirmation email via either Outlook or Gmail.

  You can embed the form directly into your website and route all submissions to your preferred Slack channel for quick follow-up.

  ✅ Key Features

  🌐 Website Form Trigger**: A no-code form that can be embedded directly on your website.
  ⚡ Slack Integration**: Instantly posts lead details to a designated Slack channel.
  📧 Email Follow-Up (Optional)**: Sends a thank-you email to the user via either Gmail or Microsoft Outlook.
  🔗 Easy to Connect**: Requires minimal setup with OAuth for Slack and email APIs.

  🧰 What You'll Need

  Slack Bot Token & Permissions**
  Gmail or Outlook account (optional)**
  n8n instance (cloud or self-hosted)**

  🛠️ Step-by-Step Setup

  1️⃣ Embed Contact Form on Website
  Node**: Form Submission on Website
  What it does**: Captures user inputs — Name, Email, and Phone.
  How to use**:
    Grab the public webhook URL from this node.
    Embed it as a form action on your website (HTML form or no-code builder).
  API**: None required. Webhook-based.

  2️⃣ Send to Slack
  Node**: Slack
  What it does**: Posts a message to your Slack #leads channel with submission details.
  Message format**:
      You have a form submission with these details.
    Name: {{ Name }}
    Email: {{ Email }}
    Phone: {{ Phone }}
    API**: Slack Bot Token (OAuth2)

  3️⃣ Optional: Send Confirmation Email
  Node**: Send Email - Gmail
    Sends email using Gmail API.
  Node**: Send Email - Outlook
    Sends email using Microsoft Outlook API.
  Message**:
      Hi {{ Name }},

    Thank you for reaching out on our website. We'll be in touch soon!
    API**: Gmail or Microsoft Outlook OAuth2

  👤 Created By
  Robert Breen  
  Automation Consultant | AI Workflow Designer | n8n Expert  
  📧 rbreen@ynteractive.com  
  🌐 ynteractive.com  
  🔗 LinkedIn

  🏷️ Tags
  slack lead alerts website form n8n email automation real-time notification lead generation form trigger webhook

nodes_used:
  ["n8n-nodes-base.slack","n8n-nodes-base.formTrigger","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

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name: Daily Ad Spend Monitoring with Google Sheets and Slack Threshold Alerts
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-05T00:44:26.418Z
updated_at: 2025-08-05T00:44:26.418Z
url: https://n8n.io/workflows/6990
scraped_at: 2025-12-24 13:02:45
description:
  This n8n workflow checks daily ad spend totals from a Google Sheet and sends a Slack alert if spend exceeds $100. It can be scheduled to run automatically or manually triggered for testing. This is perfect for marketing teams who want to monitor budget spikes in near real-time.

  ✅ Key Features

  📥 Google Sheets Integration**: Pulls raw spend data from a shared spreadsheet.
  📆 Scheduled or Manual Execution**: Can run daily on a schedule or manually for testing.
  📈 Aggregates Spend**: Summarizes daily totals from raw data.
  🧠 Logic Check**: Alerts only when spend exceeds a certain threshold.
  🔔 Slack Alerts**: Sends instant notification to a specified channel.

  🧰 What You'll Need

  Google Cloud Project** with Sheets API enabled
  OAuth2 Credential** for Google Sheets
  Slack Bot Token** with permission to post to your workspace
  Your Google Sheet link and tab name**

  📎 Copy this Sample Google Sheet to Use:  
  Marketing Data Sheet - Copy Me

  🔧 Step-by-Step Setup

  1️⃣ Schedule or Manual Trigger
  Node**: Schedule Workflow or Test Workflow
  Purpose**: Either run daily via a cron-like rule or manually trigger the flow.

  2️⃣ Get Google Sheet Data
  Node**: Get Data
  What it does**: Fetches all rows from your connected sheet.
  Setup**:
    Go to Google Cloud Console
    Create a new project
    Enable Google Sheets API
    Create OAuth2 credentials for a desktop or web application
    Connect your Google account in n8n via OAuth2
    Grant access to the sheet you want to read (ensure it's shared with your OAuth email)
    Use the copied sheet's link when connecting in n8n

  3️⃣ Summarize Spend by Day
  Node**: Sum spend by Day
  What it does**: Groups the dataset by Date and sums the Spend ($) column
  Requirements**:
    Your sheet must have a header row with Date and Spend ($) as columns

  4️⃣ Sort by Most Recent Date
  Node**: Sort Dates Descending
  What it does**: Sorts all entries by the Date field so that the most recent day is first
  Custom JavaScript**:
  const items = $input.all();
  items.sort((a, b) =&gt; new Date(b.json.Date) - new Date(a.json.Date));
  return items;

  5️⃣ Select Top Result
  Node**: Keep only Last Day
  What it does**: Captures the top row (most recent day) for evaluation
  Fields**: Sets only Date and sum_Spend_($) to keep things clean

  6️⃣ Check Spend Threshold
  Node**: Check if Spend over $100
  What it does**: Uses an IF node to compare sum_Spend_($) against a 100 threshold
  Logic**:
  sum_Spend_($) &gt; 100

  7️⃣ Send Slack Notification
  Node**: Send Slack Message
  What it does**: Sends a message to a Slack channel if the threshold is exceeded
  Setup**:
    Go to Slack API
    Create a new app
    Enable chat:write and channels:read scopes under OAuth & Permissions
    Install the app to your workspace
    Copy the OAuth Token into your Slack credentials in n8n
    Select your target channel from the dropdown (must be public or the bot must be invited)
  Message**:
      The spend for the most recent day is over $100
  8️⃣ No Action if Under Budget
  Node**: Do Nothing. Under 100
  Purpose**: This path simply ends the flow with no action if spend is below the threshold

  👤 Created By
  Robert Breen  
  Automation Consultant | AI Workflow Designer | n8n Expert  
  📧 rbreen@ynteractive.com  
  🌐 ynteractive.com  
  🔗 LinkedIn

  🏷️ Tags
  slack marketing automation budget alert daily schedule google sheets threshold logic n8n spend tracking data summarization

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.summarize","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.slack","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Scrape Google Maps by area & Generate Outreach Messages for Lead Generation
author_name: Solomon
author_username: solomon
categories: []
created_at: 2025-08-05T06:05:50.841Z
updated_at: 2025-08-05T06:05:50.841Z
url: https://n8n.io/workflows/6993
scraped_at: 2025-12-24 13:02:41
description:
  This n8n workflow automates lead extraction from Google Maps, enriches data with AI, and stores results for cold outreach.

  It uses the Bright Data community node and Bright Data MCP for scraping and AI message generation.

  How it works

  Form Submission
      
      User provides Google Maps starting location, keyword and country.
      
  Bright Data Scraping
      
      Bright Data community node triggers a Maps scraping job, monitors progress, and downloads results.
      
  AI Message Generation
      
      Uses Bright Data MCP with LLMs to create a personalized cold call script and talking points for each lead.
      
  Database Storage
      
      Enriched leads and scripts are upserted to Supabase.
  How to use

  Set up all the credentials, create your Postgres table and submit the form. The rest happens automatically.

  Requirements

  LLM account (OpenAI, Gemini…) for API usage.
  Bright Data account for API and MCP usage.
  Supabase account (or other Postgres database) to store information.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.formTrigger","n8n-nodes-base.merge","n8n-nodes-base.postgres","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.limit","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@brightdata/n8n-nodes-brightdata.brightData","@brightdata/n8n-nodes-brightdata.brightData","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.postgres","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

workflow_json_compressed:
  [encoded data, 10912 characters]


name: AI Orchestrator: dynamically Selects Models Based on Input Type
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-08-05T10:21:49.772Z
updated_at: 2025-08-05T10:21:49.772Z
url: https://n8n.io/workflows/7004
scraped_at: 2025-12-24 13:02:41
description:
  This workflow is designed to intelligently route user queries to the most suitable large language model (LLM) based on the type of request received in a chat environment. It uses structured classification and model selection to optimize both performance and cost-efficiency in AI-driven conversations.

  It dynamically routes requests to specialized AI models based on content type, optimizing response quality and efficiency.

  Benefits

  Smart Model Routing**: Reduces costs by using lighter models for general tasks and reserving heavier models for complex needs.
  Scalability**: Easily expandable by adding more request types or LLMs.
  Maintainability**: Clear logic separation between classification, model routing, and execution.
  Personalization**: Can be integrated with session IDs for per-user memory, enabling personalized conversations.
  Speed Optimization**: Fast models like GPT-4.1 mini or Gemini Flash are chosen for tasks where speed is a priority.
  How It Works
  Input Handling:  
     The workflow starts with the "When chat message received" node, which triggers the process when a chat message is received. The input includes the chat message (chatInput) and a session ID (sessionId).

  Request Classification:  
     The "Request Type" node uses an OpenAI model (gpt-4.1-mini) to classify the incoming request into one of four categories:  
       general: For general queries.  
       reasoning: For reasoning-based questions.  
       coding: For code-related requests.  
       search: For queries requiring search tools.  
     The classification is structured using the "Structured Output Parser" node, which enforces a consistent output format.

  Model Selection:  
     The "Model Selector" node routes the request to one of four AI models based on the classification:  
       Opus 4 (Claude 4 Sonnet): Used for coding requests.  
       Gemini Thinking Pro: Used for reasoning requests.  
       GPT 4.1 mini: Used for general requests.  
       Perplexity: Used for search (Google-related) requests.  

  AI Processing:  
     The selected model processes the request via the "AI Agent" node, which includes intermediate steps for complex tasks.  
     The "Simple Memory" node retains session context using the provided sessionId, enabling multi-turn conversations.  

  Output:  
     The final response is generated by the chosen model and returned to the user.  

  Set Up Steps
  Configure Trigger:  
     Ensure the "When chat message received" node is set up with the correct webhook ID to receive chat inputs.  

  Define Classification Logic:  
     Adjust the prompt in the "Request Type" node to refine classification accuracy.  
     Verify the output schema in the "Structured Output Parser" node matches expected categories (general, reasoning, coding, search).  

  Connect AI Models:  
     Link each model node (Opus 4, Gemini Thinking Pro, GPT 4.1 mini, Perplexity) to the "Model Selector" node.  
     Ensure credentials (API keys) for each model are correctly configured in their respective nodes.  

  Set Up Memory:  
     Configure the "Simple Memory" node to use the sessionId from the input for context retention.  

  Test Workflow:  
     Send test inputs to verify classification and model routing.  
     Check intermediate outputs (e.g., request_type) to ensure correct model selection.  

  Activate Workflow:  
     Toggle the workflow to "Active" in n8n after testing.  

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

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.modelSelector","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote"]

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name: Automate WhatsApp Sales with DeepSeek AI, Google Sheets and Gmail Notifications
author_name: Ahmed Saadawi
author_username: ahmedsaadawi
categories: []
created_at: 2025-08-05T10:24:36.993Z
updated_at: 2025-08-05T10:24:36.993Z
url: https://n8n.io/workflows/7005
scraped_at: 2025-12-24 13:02:46
description:
  Turn WhatsApp Into a 24/7 AI Sales Assistant — n8n + DeepSeek + Sheets + Gmail

  ⚠️ Self-Hosted n8n Only

  Description

  Turn your WhatsApp channel into a smart sales assistant! This workflow listens for inbound customer messages, looks up product data in Google Sheets, uses a DeepSeek Chat Model to answer in Saudi dialect, collects purchase details, and notifies your service rep only when the customer is ready to buy.

  🔧 How to Install Community Nodes

  Go to Settings → Community Nodes
  Click Install Node, then add:

  n8n-nodes-evolution-api

  Restart n8n if prompted.

  🔄 What This Workflow Does

  Webhook Listener
     Captures inbound WhatsApp messages (MESSAGES_UPSERT via Evolution API).
  Filters
     Ignores outbound (fromMe) and group (@g.us) messages.
  Data Extraction
     Pulls the customer’s message and phone number.
  AI Response
     Uses the DeepSeek Chat Model node to answer from your Google Sheets product list, greeting with “هلا وغلا” and speaking in Saudi dialect.
  Purchase Flow
     Prompts for name, phone, and delivery/pickup date.
  Notify Sales
     Sends an email via Gmail only when the customer requests to purchase.
  Context Memory
     (Optional) Stores conversation history in Postgres for coherent multi-turn chats.

  📸 Visual Preview

  🧩 Workflow 

  🛠️ Setup Instructions

  Evolution API Webhook

     In Evolution API dashboard → Events → Webhook
     Enable only MESSAGES\_UPSERT
     Set Webhook URL to:
       https://your-n8n-domain/webhook/whatsAppListen

  Google Sheets

     Create a spreadsheet (“You Conmanay Name Items”) with your product data [Item name, Item Model, Item Description, Item Components, Item Price, Item Availability, ...]
     Connect your Google Sheets credentials in n8n

  DeepSeek Chat Model

     Configure your DeepSeek API credentials in the DeepSeek Chat Model node
     Ensure the system prompt matches your company’s tone and data columns

  Gmail Notifications

     Add Gmail OAuth2 credentials to the Send a message in Gmail node
     Customize subject and email template if needed

  Postgres Memory (Optional)

     Connect a Postgres instance in the Postgres Chat Memory node for session context

  👥 Who Is This For?

  E-commerce teams** automating first-touch customer replies
  Sales reps** needing AI-driven chat support on WhatsApp
  Businesses** using WhatsApp as a primary customer channel

  🔐 Credentials Required

  Evolution API (webhook only)
  Google Sheets API
  DeepSeek API
  Gmail OAuth2
  Postgres (optional, for memory)

  🏷 Tags

  whatsapp bot, deepseek, google sheets, evolution api, gmail, postgres memory, ecommerce, sales automation, n8n template, no-code, ai, agent, ai agent

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.gmailTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.lmChatDeepSeek","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-evolution-api.evolutionApi","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryPostgresChat"]

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name: Automate SEO Analysis for Multiple Domains with Ahrefs and Google Sheets
author_name: Michael Muenzer
author_username: michaelmuenzer
categories: []
created_at: 2025-08-05T13:29:03.226Z
updated_at: 2025-08-05T13:29:03.226Z
url: https://n8n.io/workflows/7010
scraped_at: 2025-12-24 13:02:41
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  Fetch SEO and traffic information from ahref for a list of domains in a Google Sheet. This is great for marketing research and SEO workflow optimizations and saves tons of time.

  How it works
  We'll import domains from the Google sheet
  We use an SEO MCP server to fetch data from ahref free tooling
  The fetched data is stored in the Google sheet

  Set up steps
  Copy Google Sheet template and add it in all Google Sheet nodes
  Make sure that n8n has read & write permissions for your Google sheet.
  Add your list of domains in the first column in the Google sheet
  Add MCP credentials for seo-mcp

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-mcp.mcpClient","n8n-nodes-mcp.mcpClient","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Generate Images from Text with IBM Granite Vision 3.3 2B AI Model
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-05T14:23:41.808Z
updated_at: 2025-08-05T14:23:41.808Z
url: https://n8n.io/workflows/7012
scraped_at: 2025-12-24 13:02:44
description:
  Generate Images from Text with IBM Granite Vision 3.3 2B AI Model

  🌍 Overview

  This workflow uses the ibm-granite/granite-vision-3.3-2b model (hosted on Replicate) to generate AI images. It starts manually, sends a request to the Replicate API, waits for the result, and finally outputs the generated image link.

  Think of it as your AI art assistant — you click once, and it handles the full request/response cycle for image generation.

  🟢 Section 1: Trigger & API Setup

  🔗 Nodes:

  Manual Trigger* → Starts when you click *Execute.
  Set API Key** → Stores your Replicate API Key safely in the workflow.

  💡 Beginner takeaway:
  This section is like turning the key in the ignition. You start the workflow, and it loads your credentials so you can talk to Replicate’s API.

  📈 Advantage:
  Keeps your API key stored inside the workflow instead of hard-coding it everywhere.

  🟦 Section 2: Create Prediction

  🔗 Nodes:

  HTTP Request (Create Prediction)** → Sends a request to Replicate with the chosen model (granite-vision-3.3-2b) and input parameters (seed, temperature, max\_tokens, etc.).

  💡 Beginner takeaway:
  This is where the workflow actually asks the AI model to generate an image.

  📈 Advantage:
  You can tweak parameters like creativity (temperature) or randomness (seed) to control results.

  🟣 Section 3: Polling & Status Check

  🔗 Nodes:

  Extract Prediction ID (Code)** → Saves the unique job ID.
  Wait (2s)** → Pauses before checking status.
  Check Prediction Status (HTTP Request)** → Calls Replicate to see if the image is ready.
  If Condition (Check If Complete)** →

    ✅ If status = succeeded → move to result
    🔄 Else → go back to Wait and check again

  💡 Beginner takeaway:
  Since image generation takes a few seconds, this section keeps asking the AI “are you done yet?” until the image is ready.

  📈 Advantage:
  No need to guess — the workflow waits automatically and retries until success.

  🔵 Section 4: Process Result

  🔗 Nodes:

  Process Result (Code)** → Extracts the final data:

    ✅ Status
    ✅ Output image URL
    ✅ Metrics (time taken, etc.)
    ✅ Model info

  💡 Beginner takeaway:
  This section collects the finished image link and prepares it neatly for you.

  📈 Advantage:
  You get structured output that you can save, display, or use in another workflow (like auto-sending images to Slack or saving to Google Drive).

  📊 Final Overview Table

  | Section              | Nodes                              | Purpose                     | Benefit                     |
  | -------------------- | ---------------------------------- | --------------------------- | --------------------------- |
  | 🟢 Trigger & Setup   | Manual Trigger, Set API Key        | Start + load credentials    | Secure API key management   |
  | 🟦 Create Prediction | HTTP Request                       | Ask AI to generate image    | Control creativity & output |
  | 🟣 Polling           | Extract ID, Wait, Check Status, If | Repeatedly check job status | Auto-wait until done        |
  | 🔵 Process Result    | Process Result                     | Extract image + details     | Get clean output for reuse  |

  🚀 Why This Workflow is Useful

  Automates full API cycle** → From request to final image URL
  Handles delays automatically** → Keeps checking until your image is ready
  Customizable parameters** → Adjust creativity, randomness, and token limits
  Reusable** → Connect it to email, Slack, Notion, or storage for instant sharing
  Beginner-friendly* → Just plug in your API key and hit *Execute

nodes_used:
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name: Automate SEO Blog Post Creation and Publishing with OpenAI & WordPress
author_name: Khaisa Studio
author_username: khaisastudio
categories: []
created_at: 2025-08-06T06:53:21.273Z
updated_at: 2025-08-06T06:53:21.273Z
url: https://n8n.io/workflows/7038
scraped_at: 2025-12-24 13:02:45
description:
  AI WordPress - SEO Content Generator automates creating and publishing SEO-friendly blog articles on WordPress. It combines AI technologies like OpenAI and OpenRouter to craft catchy titles, write 1500+ word articles, generate natural featured images, and publish everything seamlessly. 

  This workflow turns your WordPress site into a content powerhouse that boosts traffic and saves you hours by handling the entire blog post process automatically.

  Why Use AI WordPress - SEO Content Generator?

  Save Time
  Automate the entire SEO content creation from ideation to publishing, freeing up hours weekly.

  Lose Writer's Block 
  Get fresh, unique, and engaging article ideas without stressing over topics or titles.

  Boost SEO
  Generate optimized titles, meta-descriptions, and focus keyphrases to improve search rankings and click-through rates.

  Professional Polish
  Automated featured images and structured posts make your blog look like it has a full editorial team behind it.

  Perfect For

  Content Marketers
  Streamline your content pipeline for blogs that rank and convert.

  Small Business Owners
  Keep your website fresh with relevant IT and business tech content without hiring writers.

  WordPress Users
  Anyone who wants hassle-free SEO blog posts on their WordPress site without lifting a finger.

  How It Works

  | Step | Process |
  |------|---------|
  | Trigger | Starts on schedule every 3 hours or manually via Telegram command "generate" |
  | Process | Chooses article topic and category, then crafts title, slug, keyphrases, and meta description using AI |
  | Smart Logic | Writes a long-form SEO article (1500-2500 words) with actionable, audience-focused advice and generates a natural-looking featured image to match the post |
  | Output | Publishes drafted articles to WordPress, sets featured images, and sends notifications to Discord and Telegram channels |

  Quick Setup

  Step 1: Import & Configure
  Import JSON file to your n8n instances

  Step 2: Add Credentials
  Configure the following API connections:
  WordPress API** - For publishing posts
  OpenAI API** - For article and image generation  
  OpenRouter API** - For topic generation
  Discord Webhook** - For notifications (optional)
  Telegram API** - For manual triggering (optional)

  Step 3: Customize Settings
  Adjust posting URLs and endpoints
  Configure Telegram commands
  Set content categories as needed
  Replace placeholder WordPress site URLs with your own

  Step 4: Test & Deploy
  Run the workflow manually to verify setup
  Check that posts appear correctly on your WordPress site
  Enable scheduled triggers for automation

  Requirements

  Before getting started, make sure you have:

  Active n8n instances
  WordPress account with API access
  OpenAI API key for article and image generation
  OpenRouter API key for topic generation
  Discord server webhook URL (optional)
  Telegram bot token for manual triggering (optional)

  Level Up Ideas

  Take your automation to the next level:

  Add multilingual support** for global SEO coverage
  Integrate social media posting* for automatic cross-channel promotion *Available HERE!**
  Incorporate advanced AI writing models** for even richer articles

  Get Support
  Created by: khaisa Studio
  Tags: SEO, WordPress, AI Content, Automation
  Category: Content Creation
  Need custom work? Contact me

  Start automating your blog posts today!

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name: Send a voice note on Telegram to generate a professional email with ChatGPT
author_name: Baptiste Fort
author_username: baptistefort
categories: []
created_at: 2025-08-06T08:30:25.992Z
updated_at: 2025-08-06T08:30:25.992Z
url: https://n8n.io/workflows/7041
scraped_at: 2025-12-24 13:02:45
description:
  Telegram Voice Message → Automatic Email



  Imagine: What if you could turn a simple Telegram voice message into a professional email—without typing, copying, pasting, or even opening Gmail?

  This workflow does it all for you: just record a voice note, and it will transcribe, format, and write a clean HTML email, then send it to the right person—all by itself.

  Prerequisites

  Create a Telegram bot** (via BotFather) and get the token.
  Have an OpenAI account** (API key for Whisper and GPT-4).
  Set up a Gmail account with OAuth2.**
  Import the JSON template** into your automation platform.

  🧩 Detailed Flow Architecture

  1. Telegram Trigger



  Node: Telegram Trigger  
  This node listens to all Message events received by the specified bot (e.g., “BOT OFFICIEL BAPTISTE”).  
  Whenever a user sends a voice message, the trigger fires automatically.

  &gt; ⚠️ Only one Telegram trigger per bot is possible (API limitation).

  Key parameter:  
  Trigger On: Message

  2. Wait

  Node: Wait  
  Used to buffer or smooth out calls to avoid collisions if you receive several voice messages in a row.

  3. Retrieve the Audio File



  Node: Get a file  
  Type:** Telegram (resource: file)
  Parameter:**  
    fileId = {{$json"message"["file_id"]}}  
  This node fetches the voice file from Telegram received in step 1

  4. Automatic Transcription (Whisper)



  Node: Transcribe a recording  
  Resource:** audio  
  Operation:** transcribe  
  API Key:** Your OpenAI account  
  The audio file is sent to OpenAI Whisper: the output is clean, accurate text ready to be processed.

  5. Optional Wait (Wait1)

  Node: Wait1  
  Same purpose as step 2: useful if you want to buffer or add a delay to absorb processing time.

  6. Structured Email Generation (GPT-4 + Output Parser)

  Node: AI Agent  
  This is the core of the flow:

  The transcribed text is sent to GPT-4 (or GPT-4.1-mini here, via OpenAI Chat Model)
  Prompt used:**

          You are an assistant specialized in writing professional emails.

      Based on the text below, you must: {{ $json.text }}

      Detect if there is a recipient's email address in the text (or something similar like "send to fort.baptiste.pro")
         If it’s not a complete address, complete it by assuming it ends with @gmail.com.
      Understand the user's intent (resignation, refusal, application, excuse, request, etc.)
      Generate a relevant and concise email subject, faithful to the content
      Write a professional message, structured in HTML:
         With a polite tone, adapted to the situation
         Formatted with HTML tags (`, `, etc.)
         No spelling mistakes in French
         My first name is jeremy and if the text says he is not happy, specify the wish to resign

  ⚠️ You must always return your answer in the following strict JSON format, with no extra text:
      
          {
        "email": "adresse@gmail.com",
        "subject": "Objet de l’email",
        "body": "Contenu HTML de l’email"
      }
      
  Everything is strictly validated and formatted with the Structured Output Parser node.

  7. Automatic Email Sending (Gmail)

  Node: Send a message  
  To:** {{$json.output.email}}
  Subject:** {{$json.output.subject}}
  HTML Body:** {{$json.output.body}}  
  This node takes the JSON structure returned by the AI and sends the email via Gmail, to the right recipient, with the correct subject and full HTML formatting.

  If you want to automate manual tasks, visit our French Agence automatisation 0vni.

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name: Export Amazon Product Reviews in Bulk to Google Sheets via RapidAPI
author_name: Hunyao
author_username: hun-yao
categories: []
created_at: 2025-08-06T13:17:05.340Z
updated_at: 2025-08-06T13:17:05.340Z
url: https://n8n.io/workflows/7050
scraped_at: 2025-12-24 13:02:42
description:
  What it does
  Pulls up to 700 Amazon reviews per product (recent and top-rated) and writes them straight into a Google Sheet tab you choose.

  Perfect for
  • Brand and product managers tracking sentiment
  • Marketplace sellers analysing competitor feedback
  • Agencies building product-review dashboards

  Apps used
  RapidAPI Real-Time Amazon Data, Google Sheets, n8n Form Trigger

  How it works

  Form Trigger collects brand, product and sheet info.
  Code node extracts the ASIN and builds 70 API requests (10 pages × star ratings).
  Split-in-batches loops through the request list, throttled by two Wait nodes.
  HTTP Request fetches reviews from RapidAPI.
  IF node drops empty or error responses.
  Split Out breaks arrays into single reviews.
  Google Sheets appends every review to the target tab.
  Loop continues until all pages finish.

  Setup

  Fill in Brand name, Product / Model Name, Amazon Product URL, Tab URL to insert reviews in the form.
  Grab your X-RapidAPI-Key from RapidAPI → Add as httpHeaderAuth credential.
  Connect Google Sheets OAuth2 and make the spreadsheet Anyone with the link can edit.
  Open Workflow Settings → set timezone if you plan to schedule runs.
  Hit Execute workflow or share the form link.

  Credentials
  • Real-Time Amazon Data (RapidAPI HTTP Header Auth)
  • Google Sheets OAuth2

  Limits and notes
  • \~100 RapidAPI calls for the free plan. Plan quota accordingly.
  • Assumes Amazon returns 10 pages per star rating; fewer pages skip silently.
  • Large sheets may hit Google API write quotas.


  If you have any questions in running the workflow, feel free to reach out to me at my youtube channel: https://www.youtube.com/@hunyaochong

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

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name: Automate Personalized Email Campaigns with Google Docs, Sheets and SMTP
author_name: Stéphane Heckel
author_username: stephaneheckel
categories: []
created_at: 2025-08-06T18:15:33.000Z
updated_at: 2025-08-06T18:15:33.000Z
url: https://n8n.io/workflows/7065
scraped_at: 2025-12-24 13:02:43
description:
  Emailing Using Google Sheet, Google Docs, and SMTP

  Automate personalized email campaigns using a Google Sheets contact list, a Google Docs template, and SMTP delivery.

  How It Works

  Google Docs** is used as the email template with variables: {{firstname}}, {{lastname}}, {{company}}, {{email}}.
  Google Sheet** contains your list of recipients (one per row).
  For each contact, the workflow merges personal data into the Google Docs template.
  Email is sent to each recipient via SMTP (batch size: 1). Use the Wait node to respect provider quotas.
  After sending, the workflow updates the "process" column of the Google Sheet with the date/time.

  How to Use

  Copy Templates:
     Google Docs Template
     Google Sheet Template
     Find each document’s ID (the text after /d/ and before /edit in the URL).

  Configure Workflow:
     Enter your Google Docs and Google Sheets IDs in the settings node.
     Set your email subject in the appropriate parameter.

  Set Up Credentials:
     Connect your Google account.
     Configure the SMTP node with your mail server details.

  Update Data:
     Edit the Google Docs template with your message and variables.
     Prepare your Google Sheet with these columns: email, firstname, lastname, company.

  Deploy and Test:
     Connect all nodes.
     Test with a small contact batch.
     Troubleshoot any node errors (indicated in red in n8n).

  Requirements

  Google Credentials & permissions**: For Sheets and Docs access.
  SMTP Server**: For email delivery (adjust Wait node for rate limits).
  n8n Version**: Tested on 1.105.2 (Ubuntu). 

  Need Help?

  Comment this post or contact me on LinkedIn
  Ask in the n8n Community Forum!

  See Also

  After running your email campaign, some messages may fail to deliver. This workflow scans your email inbox for delivery errors (e.g., bounced messages), flags problematic email addresses in the Google Sheet and ensures future campaigns skip them.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDocs","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.emailSend","n8n-nodes-base.filter","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.noOp","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.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: 🤖 AI-Powered Prompt Enhancement Assistant using Google Sheets
author_name: EoCi - Mr.Eo
author_username: eocimreo
categories: []
created_at: 2025-08-06T19:16:57.923Z
updated_at: 2025-08-06T19:16:57.923Z
url: https://n8n.io/workflows/7067
scraped_at: 2025-12-24 13:02:44
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  Introduction
  Tired of spending time crafting the perfect AI prompt? This workflow takes your simple ideas like "write a blog post" and automatically transforms them into detailed, structured prompts that actually work.
  🎯 What This Does
  Automatically converts simple user prompts like "write a blog post" into structured, professional AI prompts with metadata, variables, and clear instructions. Perfect for everybody, all industries and organizations who are wanting to eliminate prompt engineering works.

  🔄 How It Works
  Google Sheets Trigger monitors for new prompts
  AI Enhancement Pipeline uses Gemini + Groq to add structure & context  
  Field Completion auto-generates missing metadata (topic, categories)
  Quality Assurance validates & stores complete results
  🚀 Setup Requirements
  AI APIs**: Gemini, Telegram, Groq API keys
  Google Sheets**: 2 sheets (Main, ModifiedPrompt)
  5 minutes setup time** - detailed instructions in blue sticky notes
  Set up steps
  Setup time: &lt; 5 minutes
  Create a Google Spreadsheet with two tabs (sheets): OriginalPrompts and ModifiedPrompts.
     OriginalPrompts columns: Original Prompt ID | Model | Original Prompt | Created Time
     ModifiedPrompts columns (example): Modified Prompt ID | Original Prompt ID | Topic | Topic Categories | Modified Prompt | Prompt Title | Prompt Type | Model Used | Improvement Notes | Updated Time | Created Time | isProcessed

  Add and attach credentials in n8n:
     Google Sheets OAuth2 (required for getting new prompt)
     Gemini and Groq API credentials (required for AI Agent)
     Telegram credential (required for notifications)

  Save & Activate the workflow. Add a test row to OriginalPrompts, for example:  
     Original Prompt ID: 1 — Original Prompt: "Write a short blog post about AI ethics".

  Wait ~30–60s and check ModifiedPrompts for the enhanced output.

  That’s it ! Once it configured, drop short ideas into your sheet and get professional prompts back automatically. Your prompts get better, your AI outputs improve, and you save hours of manual prompt crafting.

nodes_used:
  ["n8n-nodes-base.set","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGroq","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.splitInBatches","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.googleSheets"]

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name: Export Dialogflow Intents with Priority Levels to Google Sheets via Telegram
author_name: Eddy Medina
author_username: troguis
categories: []
created_at: 2025-08-06T22:38:12.352Z
updated_at: 2025-08-06T22:38:12.352Z
url: https://n8n.io/workflows/7073
scraped_at: 2025-12-24 13:02:42
description:
  What does this workflow do?

  This workflow exports the names of all Dialogflow intents from your agent, together with their priority levels, directly into a Google Sheets spreadsheet.  
  It is triggered via Telegram and includes visual indicators (emojis) for priority levels.

  📜 Overview

  🔔 Activation**:  
    Triggered when a validated user sends the keyword (e.g. "backup") via Telegram.

  📥 Data Retrieval**:  
    Fetches all intents of the specified Dialogflow agent using the Dialogflow API.

  ⚙️ Processing**:  
    Transforms each intent into an n8n-compatible item.  
    Extracts the displayName and priority of each intent.  
    Assigns an emoji and descriptive label based on priority tier:  
      🔴 Highest, 🟠 High, 🔵 Normal, 🟢 Low, 🚫 Ignore.

  📑 Storage**:  
    Appends each intent (name, priority number, emoji, and description), along with current date and time, to a Google Sheets document.

  📩 Notification**:  
    Sends a single confirmation message to the Telegram user once insertion is complete (using Execute Once).

  🛠️ How to install and configure

  Import the workflow: Upload the .json into your n8n instance.

  Connect Telegram:  
     Add your Telegram bot credentials and configure the node Validación de usuario por ID with your Telegram ID.

  Configure Dialogflow:  
     Authenticate using a Google Service Account API Credential.  
     Then, in the Obtiene datos de los intents node, replace the example project ID (TU_PROJECT_ID) with your actual Dialogflow agent's project ID.

  Connect Google Sheets:  
     Authorize Google Sheets via OAuth2 and select your destination document/sheet in the node Añadir fila en la hoja.

  Customize trigger keyword:  
     Adjust the command text (default "backup") if needed.
  Activate workflow:  
     Ensure the webhook is correctly set up in Telegram before enabling the workflow.

  👥 Who is this for?

  🤖 Bot administrators who need quick backups of Dialogflow intent names.

  🌐 Teams managing multilingual or multi-intent agents wanting priority oversight.

  💻 Development teams needing an automated way to audit or version intent configurations regularly.

  💡 Use Cases

  ⚙️ Backup intents periodically to monitor changes over time.
  📊 Visualize priority assignment in a spreadsheet for analysis or team discussion.

  📖 Document conversational structure for onboarding or knowledge transfer.

nodes_used:
  ["n8n-nodes-base.telegramTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.code"]

workflow_json_compressed:
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name: CYBERPULSE AI GRC: Automate PCI DSS Control Evaluation and Compliance Tracking
author_name: Adnan Tariq
author_username: adnantariq
categories: []
created_at: 2025-08-07T01:05:02.961Z
updated_at: 2025-08-07T01:05:02.961Z
url: https://n8n.io/workflows/7077
scraped_at: 2025-12-24 13:02:45
description:
  Description

  Automatically evaluates PCI DSS control responses using logic or AI. Designed to speed up compliance workflows, reduce audit fatigue, and flag non-compliance early.

  Who’s It For:

  Internal compliance teams
  PCI DSS auditors
  Security officers preparing for certification
  How It Works:
  Reads PCI controls and responses from Google Sheet
  Applies logic to classify each control as Compliant, Partial, or Non-Compliant
  Tags evaluation results
  Sends output to Sheet, Email, or Drive

  Requirements:

  Google Sheet with PCI controls
  n8n (open-source automation tool)
  Optional: Gmail or Drive node for delivery
  Google Sheet Requirements:
  Columns: Control_ID, Control_Description, Response, Evaluation_Result, Notes
  Headers must be in row 1

  File Templates:

  PCI_Control_Evaluation_Template.xlsx
  Customization Tips:
  Adjust logic for more strict evaluation
  Highlight non-compliant results for rapid review

  Compliance Alignment:
  • PCI DSS v4.0
  • ISO 27001 – Annex A crosswalk
  • Internal audit programs

  Setup Instructions:
  Fill in the Google Sheet template
  Connect to n8n with Google Sheet node
  Run the workflow or schedule via Cron node
  Review and export results


  🌐 https://cyberpulsesolutions.com
  📧 info@cyberpulsesolutions.com

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

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name: CYBERPULSE AI GRC: Automated ISO 42001 Compliance Evaluation
author_name: Adnan Tariq
author_username: adnantariq
categories: []
created_at: 2025-08-07T01:18:21.989Z
updated_at: 2025-08-07T01:18:21.989Z
url: https://n8n.io/workflows/7078
scraped_at: 2025-12-24 13:02:45
description:
  Description
  Automatically evaluates and maps AI governance responses to ISO 42001:2023 clause requirements using AI-powered logic. Designed for GRC consultants, audit teams, and AI-focused security programs to reduce time spent on manual clause interpretation and alignment.

  Who’s It For:
  GRC Consultants handling AI governance controls

  Internal Auditors preparing for ISO 42001 audits

  Security teams implementing AI assurance frameworks

  Organizations adopting Responsible AI principles

  How It Works:
  Triggers manually or on schedule (e.g., clause review cycles)

  Reads AI control responses from a connected Google Sheet

  Uses AI to evaluate each response against ISO 42001 clauses

  Flags compliance status (match / partial / gap) with clause mapping

  Outputs a clean control map with automated summary

  Requirements:
  Gmail or SMTP node for email

  Google Sheets connected (OAuth)

  OpenAI or AI node (optional but recommended for advanced clause interpretation)

  Google Sheet Requirements:
  Columns: ClauseID, Clause_Description, Control_Response, Evaluation_Result

  Each row must correspond to one ISO 42001 clause

  Headers in the first row

  Optional: add column for Suggested_Remediation

  File Templates:
  ISO42001_Mapping_Template.xlsx

  Includes: clause ID, clause text, response, result, suggested fix

  Customization Tips:
  Modify clause response logic in the evaluation node (e.g., strict vs lenient mapping)

  Enable multi-framework mapping (e.g., align to NIST AI RMF as well)

  Auto-send mapping result to Drive or S3 as audit evidence

  Ethics & Compliance:
  This module assists with clause interpretation and reporting only. It does not simulate AI models or assess ethical risk directly. For internal reporting, policy alignment, and audit preparation use only.

  Setup Instructions:
  Copy the provided Google Sheet template (ISO42001_Mapping_Template.xlsx)

  Fill in your control responses (row = clause)

  Connect Google Sheets node using OAuth credentials

  In the AI node:

  Evaluate clause response using GPT or internal prompt

  Flag match/partial/gap

  Optional: auto-send report via email or upload to storage

  Review results and update your compliance register accordingly

  Supports:
  ISO 42001:2023

  AI Governance Principles (OECD, NIST AI RMF)

  SOCI Act compliance efforts (AI assurance layer)

  ACSC AI oversight recommendations

  📬 info@cyberpulsesolutions.com
  🌐 https://www.cyberpulsesolutions.com/

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name: CYBERPULSE AI GRC: Automate Compliance Audit Documentation
author_name: Adnan Tariq
author_username: adnantariq
categories: []
created_at: 2025-08-07T01:36:02.682Z
updated_at: 2025-08-07T01:36:02.682Z
url: https://n8n.io/workflows/7079
scraped_at: 2025-12-24 13:02:45
description:
  Description
  Automatically packages audit-ready evidence files matched to control IDs from ISO 42001 or other frameworks.
  Fetches logs from Google Sheets, finds corresponding files in Google Drive, compresses them into a ZIP archive, and sends via email — no manual formatting required.

  Who’s It For:

  Compliance teams preparing audit documentation

  GRC consultants managing multiple clients

  Internal auditors requiring traceable evidence

  How It Works:

  Trigger manually or on schedule (e.g., daily)

  Reads audit logs from Google Sheets

  Searches Google Drive for files matching control_id

  Downloads matched files

  Zips them into an archive

  Sends the archive via email (Gmail or SMTP)

  Requirements:

  Gmail or SMTP node for email delivery

  Google Sheets connected (OAuth2)

  Google Drive connected (OAuth2)

  Google Sheet Requirements:

  Columns: control_id, description, evidence_status, last_updated

  One row per control ID or log entry

  Headers must be in the first row

  Log sheet must be shared with your service account or n8n-connected user

  File Templates:

  Audit_AutoPack_Sheet_Template.xlsx

  Evidence files in Google Drive named using control ID (e.g., ISO42001-5.1.pdf)

  Customization Tips:

  Adjust ZIP archive name in the “Zip Files” node

  Customize email subject, body, and recipient

  Use a different Drive folder per client or audit phase

  Ethics & Compliance:

  Ensures audit trail and evidence traceability

  Prevents unauthorized edits or file mismatches

  Setup Instructions

  Copy the provided Google Sheet template (linked in File Templates).

  Fill in your audit logs (columns: control_id, description, status, last_updated).

  Connect Google Sheets node using OAuth credentials.

  In the Gmail node:

  Set recipient email (e.g., your_email@example.com)

  Choose “Send binary data” and attach ZIP

  Trigger via Cron node (e.g., daily) or manually

  (Optional) Connect Drive or S3 node to store a backup copy

  Supports:

  ISO 42001 AI Governance

  PCI DSS v4.0

  NIST CSF / SOCI Act

  ACSC Essential Eight


  https://cyberpulsesolutions.com

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name: Generate Text-to-Video & Image-to-Video Content with Seedance 1 Lite AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-07T05:25:17.144Z
updated_at: 2025-08-07T05:25:17.144Z
url: https://n8n.io/workflows/7098
scraped_at: 2025-12-24 13:02:44
description:
  Generate Text-to-Video & Image-to-Video Content with Seedance 1 Lite AI

  Built with n8n + Replicate

  This workflow takes a prompt (and optional seed), sends it to Bytedance’s seedance-1-lite model, waits for processing, and returns a generated video.

  ⚡ Section 1: Start & Authenticate

  ▶️ On clicking ‘execute’** → Manual trigger to start the workflow.
  🔑 Set API Key** → Stores your Replicate API key so all requests are authorized.

  Benefit: Keeps your API credentials secure and reusable.

  🛠️ Section 2: Send Video Generation Request

  📡 Create Prediction** → Makes a POST request to Replicate with:

    prompt: your text description of the video
    seed: (optional) controls randomness for reproducibility
    Model version: b6519549e375404f45af5ef2e4b01f651d4014f3b57d3270b430e0523bad9835

  Benefit: Kickstarts AI video generation from just a simple text prompt.

  🔍 Section 3: Track the Prediction

  📦 Extract Prediction ID** → Stores predictionId, status, and predictionUrl for polling.
  ⏳ Wait** → Pauses 2 seconds between checks.
  🔁 Check Prediction Status** → Calls Replicate to see if the video is ready.
  ✅ Check If Complete** → Branches:

    If status = succeeded → continue.
    Else → loop back to Wait until it’s finished.

  Benefit: Ensures the workflow patiently monitors progress without timing out.

  📽️ Section 4: Process & Return Results

  📦 Process Result** → Outputs a clean response containing:

    status
    video_url (generated video)
    metrics
    created_at & completed_at
    model: bytedance/seedance-1-lite

  Benefit: Gives you structured data and the direct video link, ready to share or store.

  📊 Workflow Overview

  | Section             | Purpose                     | Key Nodes                                     | Benefit                         |
  | ------------------- | --------------------------- | --------------------------------------------- | ------------------------------- |
  | ⚡ Start & Auth      | Initialize & secure API key | Manual Trigger, Set API Key                   | Keeps credentials safe          |
  | 🛠️ Send Request    | Start video generation      | Create Prediction                             | Submits prompt to Replicate     |
  | 🔍 Track Prediction | Poll status until done      | Extract Prediction ID, Wait, Check Status, If | Reliable async handling         |
  | 📽️ Process Result  | Format output               | Process Result                                | Easy access to final video link |

  ✅ Final Benefits

  🎬 Generate AI-powered videos directly from text prompts.
  🔑 API key stored securely within workflow.
  🔄 Handles asynchronous processing with automatic polling.
  📤 Provides clean, ready-to-use JSON output including video URL.
  🧩 Flexible — you can connect results to Slack, Google Drive, or YouTube for instant publishing.

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name: Generate 3D Models & Textures from Images with Hunyuan3D AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-07T05:30:45.472Z
updated_at: 2025-08-07T05:30:45.472Z
url: https://n8n.io/workflows/7111
scraped_at: 2025-12-24 13:02:44
description:
  Generate 3D Models & Textures from Images with Hunyuan3D AI

  This workflow connects n8n → Replicate API to generate 3D-like outputs using the ndreca/hunyuan3d-2.1-test model. It handles everything: sending the request, waiting for processing, checking status, and returning results.

  ⚡ Section 1: Trigger & Setup

  ⚙️ Nodes

  1️⃣ On Clicking “Execute”

  What it does:** Starts the workflow manually in n8n.
  Why it’s useful:** Great for testing or one-off runs before automation.

  2️⃣ Set API Key

  What it does:* Stores your *Replicate API Key**.
  Why it’s useful:** Keeps authentication secure and reusable across HTTP nodes.

  💡 Beginner Benefit

  No coding needed — just paste your API key once.
  Easy to test: press Execute, and you’re live.

  🤖 Section 2: Send Job to Replicate

  ⚙️ Nodes

  3️⃣ Create Prediction (HTTP Request)

  What it does:* Sends a *POST request** to Replicate’s API with:

    Model version (70d0d816...ae75f)
    Input image URL
    Parameters like steps, seed, generate_texture, remove_background
  Why it’s useful:** This kicks off the AI generation job on Replicate’s servers.

  4️⃣ Extract Prediction ID (Code)

  What it does:* Grabs the *prediction ID** from the API response and builds a status-check URL.
  Why it’s useful:** Every job has a unique ID — this lets us track progress later.

  💡 Beginner Benefit

  You don’t need to worry about JSON parsing — the workflow extracts the ID automatically.
  Everything is reusable if you run multiple generations.

  ⏳ Section 3: Poll Until Complete

  ⚙️ Nodes

  5️⃣ Wait (2s)

  What it does:** Pauses for 2 seconds before checking the job status.
  Why it’s useful:** Prevents spamming the API with too many requests.

  6️⃣ Check Prediction Status (HTTP Request)

  What it does:** GET request to see if the job is finished.

  7️⃣ Check If Complete (IF Node)

  What it does:**

    If status = succeeded → process results.
    If not → loops back to Wait and checks again.

  💡 Beginner Benefit

  Handles waiting logic for you — no manual refreshing needed.
  Keeps looping until the AI job is really done.

  📦 Section 4: Process the Result

  ⚙️ Nodes

  8️⃣ Process Result (Code)

  What it does:** Extracts:

    status
    output (final generated file/URL)
    metrics (performance stats)
    Timestamps (created_at, completed_at)
    Model info
  Why it’s useful:** Packages the response neatly for storage, email, or sending elsewhere.

  💡 Beginner Benefit

  Get clean, structured data ready for saving or sending.
  Can be extended easily: push output to Google Drive, Notion, or Slack.

  📊 Workflow Overview

  | Section               | What happens                      | Key Nodes                     | Benefit                           |
  | --------------------- | --------------------------------- | ----------------------------- | --------------------------------- |
  | ⚡ Trigger & Setup     | Start workflow + set API key      | Manual Trigger, Set           | Easy one-click start              |
  | 🤖 Send Job           | Send input & get prediction ID    | Create Prediction, Extract ID | Launches AI generation            |
  | ⏳ Poll Until Complete | Waits + checks status until ready | Wait, Check Status, IF        | Automated loop, no manual refresh |
  | 📦 Process Result     | Collects output & metrics         | Process Result                | Clean result for next steps       |

  🎯 Overall Benefits

  ✅ Fully automates Replicate model runs
  ✅ Handles waiting, retries, and completion checks
  ✅ Clean final output with status + metrics
  ✅ Beginner-friendly — just add API key + input image
  ✅ Extensible: connect results to Google Sheets, Gmail, Slack, or databases

  ✨ In short: This is a no-code AI image-to-3D content generator powered by Replicate and automated by n8n.

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name: Generate Images with Realistic Inpainting using Simbrams Ri AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-07T05:31:35.575Z
updated_at: 2025-08-07T05:31:35.575Z
url: https://n8n.io/workflows/7113
scraped_at: 2025-12-24 13:02:45
description:
  Generate Images with Realistic Inpainting using Simbrams Ri AI

  This n8n workflow integrates with Replicate’s simbrams/ri model to generate images. It takes an input image and mask, applies transformations based on your parameters, and returns the final generated output automatically.

  📌 Section 1: Trigger & Authentication

  ⚡ On Clicking ‘Execute’ (Manual Trigger)

  Purpose**: Starts the workflow manually.
  Benefit**: Useful for testing and running on demand.

  🔑 Set API Key (Set Node)

  Purpose: Stores your **Replicate API key inside the workflow.
  Benefit**: Keeps credentials secure and ensures other nodes can reuse them.

  📌 Section 2: Sending the Image Generation Request

  🖼️ Create Prediction (HTTP Request Node)

  Purpose**: Sends a POST request to Replicate’s API to start generating an image.
  Input Parameters**:

    image: Input image URL
    mask: Mask image URL
    seed: Randomness control (for reproducibility)
    steps: Number of refinement steps
    strength: Intensity of modification (0–1)
    blur\_mask: Whether to blur the mask edges
    merge\_m\_s: Whether to merge mask with source
  Benefit**: Gives full control over how the model modifies your image.

  🆔 Extract Prediction ID (Code Node)

  Purpose: Extracts the **Prediction ID, status, and URL from Replicate’s response.
  Benefit**: Required to check the status of the generation later.

  📌 Section 3: Polling & Waiting

  ⏳ Wait (Wait Node)

  Purpose**: Pauses the workflow for 2 seconds before rechecking.
  Benefit**: Prevents hitting Replicate’s API too quickly.

  🔄 Check Prediction Status (HTTP Request Node)

  Purpose**: Checks whether the prediction is complete using the stored Prediction ID.
  Benefit**: Automates monitoring of job progress.

  ✅ Check If Complete (If Node)

  Purpose**: Decides if the prediction has finished.
  Paths**:

    True → Sends result to processing.
    False → Loops back to Wait and keeps checking.
  Benefit**: Ensures the workflow only ends when a valid image is ready.

  📌 Section 4: Processing the Result

  📦 Process Result (Code Node)

  Purpose**: Cleans up the completed API response and extracts:

    Status
    Output (final generated image)
    Metrics
    Created & completed timestamps
    Model name (simbrams/ri)
    Final image URL
  Benefit**: Delivers a structured and ready-to-use result for display, storage, or further automation.

  📊 Workflow Overview Table

  | Section           | Node Name               | Purpose                              |
  | ----------------- | ----------------------- | ------------------------------------ |
  | 1. Trigger & Auth | On Clicking ‘Execute’   | Starts the workflow manually         |
  |                   | Set API Key             | Stores API credentials               |
  | 2. AI Request     | Create Prediction       | Sends image generation request       |
  |                   | Extract Prediction ID   | Extracts ID + status for tracking    |
  | 3. Polling        | Wait                    | Adds delay between checks            |
  |                   | Check Prediction Status | Monitors job progress                |
  |                   | Check If Complete       | Routes based on job completion       |
  | 4. Result         | Process Result          | Extracts and cleans the final output |

  🎯 Key Benefits

  🔐 Secure authentication with API key management.
  🖼️ Custom image generation with parameters like mask, strength, and steps.
  🔄 Automatic polling ensures results are fetched only when ready.
  📦 Clean structured output with final image URL for easy use.

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name: Build Targeted Prospect Lists: Find & Enrich Leads with Surfe to HubSpot
author_name: go-surfe
author_username: go-surfe
categories: []
created_at: 2025-08-07T11:18:02.174Z
updated_at: 2025-08-07T11:18:02.174Z
url: https://n8n.io/workflows/7130
scraped_at: 2025-12-24 13:02:41
description:
  🚀 Build Hyper-Targeted Prospecting Lists with Surfe & HubSpot

  This template automatically discovers companies that match your Ideal Customer Profile (ICP), finds the right people inside those companies and enriches them — ready to drop straight into HubSpot. Launch the workflow, sit back, and get a clean list of validated prospects in minutes.

  1. ❓ What Problem Does This Solve?

  Sourcing prospects that truly fit your ICP is slow and repetitive. You jump between databases, copy domains, hunt down decision-makers, and then still have to enrich emails and phone numbers one by one.

  This workflow replaces all that manual effort:

  It queries Surfe’s database for companies that match your exact industry, size, revenue and geography filters.
  It pulls the best-fit people inside each company and enriches them in bulk.
  It keeps only records with both a direct email and mobile phone, then syncs them to HubSpot automatically.

  No spreadsheets, no copy-paste — just a fresh, qualified prospect list ready for outreach.

  2. 🧰 Prerequisites

  You’ll need:

  A self-hosted or cloud instance of n8n
  A Surfe API Key
  A HubSpot Private App Token with contact read/write scopes
  A Gmail account (OAuth2) for the completion notification
  The workflow JSON file linked above
      
      N8N_FLOW_2__Building_Prospecting_Lists.json
  3. 📌 Search ICP Companies Configuration — Fine-Tune Your Targeting

  3.1 Editing the JSON

  Every targeting rule lives inside the “🔍 Search ICP Companies” HTTP node.

  Open the node Search ICP Companies → Parameters tab → JSON Body to edit the filters.

  | Filter | JSON path | What it does | Example |
  | --- | --- | --- | --- |
  | industries | filters.industries | Narrow to specific verticals (case-sensitive strings) | ["Software","Apps","SaaS"] |
  | employeeCount.from / to | filters.employeeCount | from / to  | 1 / 35 |
  | countries | filters.countries | 2-letter ISO codes | ["FR","DE"] |
  | revenues | filters.revenues | Annual revenue brackets | ["1-10M"] |
  | limit | limit | Companies per run | 20 |

  3.2 Where to find allowed values

  Surfe exposes an “🗂 Get Filters” endpoint that returns every accepted value for:

  industries
  employeeCounts
  revenues
  countries (always ISO-2 codes)

  You can hit it with a simple GET /v1/people/search/filters request or browse the interactive docs here:

  https://developers.surfe.com/public-008-people-filters developers.surfe.com

  For company-level searches, the same enumerations apply.

  4. ⚙️ Setup Instructions

  4.1 🔐 Create Your Credentials in n8n

  4.1.1 🚀 Surfe API

  In your Surfe dashboard → Use Surfe Api → copy your API key
  Go to n8n → Credentials → Create Credential
      Choose Credential Type: Bearer Auth
      Name it something like SURFE API Key
      Paste your API key into the Bearer Token
      Save
  4.1.2 📧 Gmail OAuth2 API

  Go to n8n → Credentials
  Create new credentials:
      Type: Gmail OAuth2 API
  A pop-up window will appear where you can log in with your Google account that is linked to Gmail
      Make sure you grant email send permissions when prompted

  4.1.3 🎯 HubSpot

  🔓 Private App Token

  Go to HubSpot → Settings → Integrations → Private Apps
      Create an app with scopes:
          crm.objects.contacts.read
          crm.objects.contacts.write
          crm.schemas.contacts.read
      Save the App token
  Go to n8n → Credentials → Create Credential → HubSpot App Token
      Paste your App Token

  ✅ You are now all set for the credentials

  4.2 📥 Import and Configure the N8N Workflow

  Import the provided JSON workflow into N8N
      Create a New Blank Workflow
      click the … on the top left
      Import from File

  4.2.1 🔗 Link Nodes to Your Credentials

  In the workflow, link your newly created credentials to each node of this list :

  Surfe HTTP nodes:
      Authentication → Generic Credential Type
      Generic Auth Type → Bearer Auth
      Bearer Auth → Select the credentials you created before
  Gmail Node Credentials to connect with → Gmail account
  Hubspot Node →Credentials to connect with → Gmail account



  Surfe HTTP nodes

  Surfe HTTP nodes

  HubSpot node → Credentials to connect with → select your HubSpot credentials in the list

  5. 🔄 How This N8N Workflow Works

  Manual Trigger – Click Execute Workflow (or schedule it) to start.
  Search ICP Companies – Surfe returns company domains that match your filter set.
  Prepare JSON Payload with Company Domains – Formats the domain list for the next call.
  Search People in Companies – Finds people inside each company.
  Prepare JSON Payload Enrichment Request – Builds the bulk-enrichment request.
  Surfe Bulk Enrichments API – Launches one enrichment job for the whole batch.
  Wait + Polling loop – Checks job status every 3 seconds until it’s COMPLETED.
  Extract List of People – Pulls the enriched contacts from Surfe’s response.
  Filter: phone AND email – Keeps only fully reachable prospects (email and mobile).
  HubSpot: Create or Update – Inserts/updates each contact in HubSpot.
  Gmail – Sends you a “Your ICP prospecting enrichment is done” email.

  6. 🧩 Use Cases

  Weekly prospect list refresh** – Generate 50 perfectly-matched prospects every Monday morning.
  Territory expansion** – Spin up a list of SMB software CEOs in a new country in minutes.
  ABM prep** – Build multi-stakeholder buying-group lists for target accounts.
  Campaign-specific lists** – Quickly assemble contacts for a limited-time product launch.

  7. 🛠 Customization Ideas

  prepare 

  🎯 Refine filters for people – Add seniorities or other filters in the node JSON PAYLOAD WITH Company Domains
      use the surfe search people api doc https://developers.surfe.com/public-009-search-people-v2
  ♻️ Deduplicate – Check HubSpot first to skip existing contacts.
  🟢 Slack alert – Replace Gmail with a Slack notification.
  📊 Reporting – Append enriched contacts to a Google Sheet for analytics.

  8. ✅ Summary

  Fire off the workflow, and n8n will find ICP-fit companies, pull key people, enrich direct contact data and drop everything into HubSpot — all on autopilot.

  Prospecting lists, done for you.

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name: AI-Powered Cold Call Machine with LinkedIn, OpenAI & Sales Navigator
author_name: Matthieu
author_username: yaznow
categories: []
created_at: 2025-08-07T15:57:48.030Z
updated_at: 2025-08-07T15:57:48.030Z
url: https://n8n.io/workflows/7140
scraped_at: 2025-12-24 13:02:41
description:
  🔧 AI-Powered Cold Call Machine

  🎯 Purpose
  The AI-Powered Cold Call Machine is a fully automated workflow designed to generate qualified leads from LinkedIn, evaluate them using AI-based scoring, identify key decision-makers, and generate personalized cold call scripts. All results are saved to a Google Sheet-based CRM.

  ⚙️ How It Works

  1. Initialization
  Triggered either manually or via schedule.
  Pulls configuration from a Google Sheet’s Settings tab (e.g., target product, keywords, company size, API key).

  2. Company Search on LinkedIn
  Uses the Ghost Genius API to search for companies based on cleaned, relevant keywords extracted by OpenAI.
  Handles pagination, up to 1000 companies per batch.

  3. Company Filtering
  Each company goes through:
  Data enrichment via Ghost Genius (website, size, followers, etc.).
  Filtering:
    Must have a LinkedIn page with a website.
    Must have 200+ followers.
  Deduplication: checks if the company already exists in the CRM.

  4. AI-Based Company Scoring
  A specialized AI model scores each company from 0 to 10 based on:
    Industry fit.
    Size/location alignment.
    Potential pain points that match your offering.
  If the company is new and relevant (score ≥ 7), it is saved in the Companies sheet.

  5. Decision Maker Identification
  Uses Sales Navigator API (via Ghost Genius) to find employees with targeted job titles.
  For each matching profile:
    Enriches contact data (title, bio, etc.).
    Retrieves phone number (if available).
    Generates a 20-second personalized cold call script using OpenAI, based on company and profile data.
    Saves all information in the Leads tab of the CRM.

  If no decision maker is found, the company status is marked accordingly.

  📈 Outcome
  A fully enriched, qualified lead database.
  Custom cold call scripts** ready to be used by SDRs or founders.
  Zero manual work – from search to lead generation, everything is automated.

  💡 Use Case
  Perfect for SDRs, founders, or growth marketers looking to scale cold outreach without sacrificing personalization or running into LinkedIn scraping limits.

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name: Beginner AI Dataset Generator using OpenAI + LangChain in n8n
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-08T00:01:14.904Z
updated_at: 2025-08-08T00:01:14.904Z
url: https://n8n.io/workflows/7154
scraped_at: 2025-12-24 13:02:41
description:
  This n8n workflow dynamically generates a realistic sample dataset based on a single topic you provide. It uses OpenAI (via LangChain) and n8n’s built-in nodes to:

  Generate structured JSON data for 5 columns with 3–5 values each  
  Flatten that data into a single text blob  
  Infer meaningful column names via a second AI call  
  Pivot, split, merge, and rename columns automatically  
  Output a clean, labeled dataset ready for export or further processing  

  ⚙️ Prerequisites

  OpenAI API Key  
     Visit: https://platform.openai.com/account/api-keys  
     Create a new key  
     In n8n: Credentials → New → OpenAI API, paste key, name it “OpenAi account”  

  LangChain nodes enabled in your n8n instance  

  🥇 Step 1: Set Up OpenAI Credential
  Go to OpenAI API Keys  
  Create and copy your key  
  In n8n: Credentials → New → OpenAI API → paste key as “OpenAi account”

  🥈 Step 2: Manual Trigger
  Add Manual Trigger to start the workflow

  🥉 Step 3: Set Topic
  Add a Set node named Set Topic to Search  
  Field: Topic = n8n use cases (or any topic you choose)

  ✨ Step 4: Generate Structured Data
  LangChain Agent** node Generate Random Data
  Connect to OpenAI Chat Model1 and Tool: Inject Creativity1  
  System prompt: instruct AI to output 5 columns of realistic values in JSON  

  🔧 Step 5: Parse AI Output
  Structured Output Parser** to validate JSON  

  🔄 Step 6: Flatten Data
  Code** node Outpt all Data to One Field  
  Joins all values into a comma-separated string for column naming

  🧠 Step 7: Generate Column Names
  LangChain Agent** Generate Column Names  
  Connect to OpenAI Chat Model2  
  Prompt: infer 5 column names from the string  

  🔢 Step 8: Pivot Names Row
  Code** node Pivot Column Names transforms array into { column1: name1, … }

  🪓 Step 9: Split Columns
  5 SplitOut nodes to break each array back into rows per column

  🔗 Step 10: Merge Rows
  Merge** node Merge Columns together using combineByPosition  

  🏷️ Step 11: Rename Columns
  Set** node Rename Columns assigns the AI-generated names to each column

  🔗 Step 12: Final Output
  Merge** Append Column Names combines data and header row

  🏁 Done! You now have a fully AI-driven, labeled dataset generated from a single topic—no external services needed. Easily extend by adding a Google Sheets or HTTP node to export.

  📬 Need Help or Want to Customize This?
  📧 robert@ynteractive.com  
  🔗 LinkedIn

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name: Get Started with Google Sheets in n8n
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-08T00:26:22.819Z
updated_at: 2025-08-08T00:26:22.819Z
url: https://n8n.io/workflows/7156
scraped_at: 2025-12-24 13:02:41
description:
  A hands-on starter workflow that teaches beginners how to:

  Pull rows from a Google Sheet

  Append a new record that mimics a form submission

  Generate AI-powered text with GPT-4o based on a “Topic” column

  Write the AI output back into the correct row using an update operation

  Along the way you’ll learn the three essential Google Sheets operations in n8n (read → append → update), see how to pass sheet data into an OpenAI node, and document each step with sticky-note instructions—perfect for anyone taking their first steps in no-code automation.

  0️⃣ Prerequisites
  Google Sheets**
    Open Google Cloud Console → create / select a project.  
    Enable Google Sheets API under APIs & Services.  
    Create an OAuth Desktop credential and connect it in n8n.  
    Share the spreadsheet with the Google account linked to the credential.
  OpenAI**
    Create a secret key at &lt;https://platform.openai.com/account/api-keys&gt;.  
    In n8n → Credentials → New → choose OpenAI API and paste the key.
  Sample sheet to copy** (make your own copy and use its link)  
    &lt;https://docs.google.com/spreadsheets/d/15i9WIYpqc5lNd5T4VyM0RRptFPdi9doCbEEDn8QglN4/edit?usp=sharing&gt;

  1️⃣ Trigger  
  Manual Trigger – lets you run on demand while learning.  
  (Swap for a Schedule or Webhook once you automate.)

  2️⃣ Read existing rows  
  Node:** Get Rows from Google Sheets  
  Reads every row from Sheet1 of your copied file.

  3️⃣ Generate a demo row  
  Node:** Generate 1 Row of Data (Set node)  
  Pretends a form was submitted:  
    Name, Email, Topic, Submitted = "Yes"

  4️⃣ Append the new row  
  Node:** Append Data to Google  
  Operation append → writes to the first empty line.

  5️⃣ Create a description with GPT-4o  
  OpenAI Chat Model – uses your OpenAI credential.  
  Write description (AI Agent) – prompt = the Topic.  
  Structured Output Parser – forces JSON like: { "description": "…" }.

  6️⃣ Update that same row  
  Node:** Update Sheets data  
  Operation update.  
  Matches on column Email to update the correct line.  
  Writes the new Description cell returned by GPT-4o.

  7️⃣ Why this matters  
  Demonstrates the three core Google Sheets operations: read → append → update.  
  Shows how to enrich sheet data with an AI step and push the result right back.  
  Sticky Notes provide inline docs so anyone opening the workflow understands the flow instantly.

  👤 Need help?  
  Robert Breen – Automation Consultant  
  ✉️ robert.j.breen@gmail.com  
  🔗 &lt;https://www.linkedin.com/in/robert-breen-29429625/&gt;

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