Browse 13,012 Workflows

By Kanaka Kishore Kandregula

Automatically identifies and reports Magento 2 orders stuck for the past 7 business days. Sends a weekly email alert to the store manager with a Google Sheets report, helping streamline order follow-ups and prevent fulfilment delays. 🔍 What It Does: This n8n automation identifies Magento 2 orders that have been stuck in the same status (like "processing") for the past 7 weekdays (excluding weekends), compiles them into a clean Google Sheet report, and emails the store manager every Monday morning with a snapshot and link to the full data for immediate action. ⚙️ Technical Highlights: Automatically runs every Monday at 8 AM using the Schedule Trigger. Dynamically calculates business days only (excluding weekends) to identify stale orders. Fetches order data using Magento 2 REST API. Filters and formats key details like customer name, order value, phone, and email. Stores the data in a Google Sheet titled with the current date. Sends a professionally formatted HTML email to the manager with: A summary table of stuck orders. A button linking directly to the full Google Sheet report. ✅ Ideal For: Magento 2 store owners/managers who need better visibility on stuck or delayed orders. Operations teams who want to avoid lost revenue or customer complaints due to order inaction. Automation engineers looking to integrate Google Workspace and Magento efficiently using n8n. 📈 Why This Matters in the Current Market: In e-commerce, stuck orders = lost trust and lost revenue. As fulfillment expectations continue to rise, proactively managing delayed or idle orders is crucial. This workflow empowers store managers to act fast, reduce manual monitoring, and keep operations smooth — all while preserving customer satisfaction and operational reputation. 🔧 Modules Used: Schedule Trigger HTTP Request (Magento 2 REST API) Code (JavaScript logic for date filtering, formatting) Google Sheets (Create & Append rows) Gmail (Send custom HTML email) Set/Get Logo (optional media path fetch for branding) 💼 Use Cases: Weekly operational check-ins for stuck orders. Root cause analysis of order processing delays. Escalation trigger for order fulfillment teams. Dashboard data feed for pending revenue reports. Enhance Magento store manager awareness with automation. 🔒 Credentials Required: Magento 2 Bearer Auth (Admin API access) Google Sheets OAuth2 (Access to Google Drive & Sheets) Gmail OAuth2 (Authorized sender account) 📂 Category: Magento 2 / E-Commerce Automation / Order Management / Reporting 💬 Need Help? If you'd like help customizing this for your Magento store, such as: Filtering by specific order statuses Adding Slack/Telegram alerts Multi-store/multi-manager support Feel free to reach out — we can assist in tailoring the workflow to your unique business logic. Contact: Author 👤 Author Kanaka Kishore Kandregula Certified Magento 2 Developer https://gravatar.com/kmyprojects https://www.linkedin.com/in/kanakakishore. An n8n automation workflow template by Kanaka Kishore Kandregula.

By Yang

📄 What this workflow does This workflow automatically turns any uploaded video into structured blog research using AI tools. It transcribes the video, extracts keywords, runs research based on those keywords, and saves the final result to a Google Sheet. It uses Dumpling AI for transcription and research, OpenAI for keyword extraction, and Google Sheets for organizing the output. 👤 Who is this for This workflow is perfect for: Content creators who repurpose video content into blog posts SEO and marketing teams looking to extract topics and keyword insights from video materials Anyone who wants to automate video-to-text and research workflows without doing it manually ✅ Requirements Google Drive** account with a folder to watch for video uploads Dumpling AI** API access for transcription and agent research OpenAI (GPT-4o)** credentials for keyword extraction Google Sheets** document with the following column headers: Keywords topicsFromPerplexity blogPostsFromGoogle ⚙️ How to set up Connect your Google Drive and choose the folder where videos will be uploaded. Set up your Dumpling AI and OpenAI GPT-4o API credentials. Create a Google Sheet with the required columns. Replace the default folder ID and spreadsheet ID in the workflow with your own. Activate the workflow to start watching for new videos. 🔁 How it works (Workflow Steps) Watch Uploaded Videos: Triggers when a new video is added to your selected Google Drive folder. Download Video: Downloads the uploaded video file. Convert Video to Base64: Prepares the video for API submission by converting it to base64. Transcribe with Dumpling AI: Sends the video to Dumpling AI to get a full transcript. Extract Keywords with OpenAI: Analyzes the transcript and extracts five key SEO keywords. Run Competitor Research via Dumpling AI: Uses those keywords to fetch related topics and blog examples from Perplexity and Google. Format Results for Google Sheets: Formats the research results into clean text blocks. Append to Google Sheets: Saves the data into your specified Google Sheet. 🛠️ Customization Ideas Add a translation step after transcription to support multilingual content research. Modify the GPT prompt to extract summaries or titles instead of keywords. Change the Google Sheet structure to log video filenames and timestamps. Add email or Slack notifications to alert you when research is complete. An n8n automation workflow template by Yang.

By Kanaka Kishore Kandregula

This workflow automates bulk price updates for Magento 2 products using data from a Google Sheet. It reads SKUs and new prices, cleans and validates the data, and updates each product via the Magento 2 REST API. Error messages from failed updates are parsed and logged clearly, making it easy to monitor and correct issues directly from the spreadsheet. Ideal for store managers and merchandisers who need a faster, error-resistant alternative to manual updates in the admin panel. ✅ What This Workflow Does: Automatically updates Magento 2 product prices in bulk using values from a Google Sheet. It reads SKU and price values, processes the data, and uses the Magento 2 REST API to push updates directly—without ever logging into the Magento admin panel. 💼 Use Cases: Magento 2 store owners or managers who frequently need to update product prices in bulk Merchandisers adjusting prices during promotions or sales events Agencies managing multiple stores looking to centralize product updates from Google Sheets Dropshipping businesses syncing supplier pricing effortlessly 🔧 Modules Used: Manual Trigger Google Sheets Function HTTP Request 🔒 Credentials Required: Google Sheets OAuth2 API Magento 2 Admin Token (via HTTP Header Auth) 📂 Category: E-Commerce / Magento 2 / Automation / Google Sheets 💬 Need Help? Having trouble setting it up or want to customize this workflow further? Feel free to reach out — I’m happy to help with setup, customization, or Magento 2 API integration issues. or 💡 Have IDEA? Please feel free to contact Auther. Happy to help. Contact: Author 👤 Author Kanaka Kishore Kandregula Certified Magento 2 Developer https://gravatar.com/kmyprojects https://www.linkedin.com/in/kanakakishore. An n8n automation workflow template by Kanaka Kishore Kandregula.

By vinci-king-01

AI Conference Intelligence & Networking Optimizer with ScrapeGraphAI > ⚠️ IMPORTANT: This template requires a self-hosted n8n instance with ScrapeGraphAI integration. It cannot be used with n8n Cloud due to web scraping capabilities. This workflow automatically discovers industry conferences and provides AI-powered networking intelligence to maximize your event ROI. How it works This workflow automatically discovers industry conferences and provides AI-powered networking intelligence to maximize your event ROI. Key Steps Scheduled Discovery - Runs weekly to find new industry conferences from Eventbrite and other sources. AI-Powered Scraping - Uses ScrapeGraphAI to extract comprehensive conference information including speakers, agenda, and networking opportunities. Speaker Intelligence - Analyzes speakers to identify high-priority networking targets based on their role, company, and expertise. Agenda Analysis - Extracts and maps the complete conference schedule to optimize your time and networking strategy. Networking Strategy - Generates AI-powered recommendations for maximizing networking ROI with prioritized contact lists and approach strategies. Set up steps Setup time: 10-15 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for web scraping capabilities. Customize conference sources - Update the Eventbrite URL to target specific industries or locations. Adjust monitoring frequency - Modify the weekly trigger to match your conference discovery needs. Review networking priorities - The system automatically prioritizes speakers, but you can customize the criteria. Technical Configuration Prerequisites Self-hosted n8n instance (version 1.0+) ScrapeGraphAI API credentials Eventbrite API access (optional, for enhanced data) API Configuration ScrapeGraphAI Setup Sign up at https://scrapegraph.ai Generate API key from dashboard Add credentials in n8n: Settings > Credentials > Add Credential > ScrapeGraphAI Customization Examples Modify Conference Sources: // In Eventbrite Scraper node, update the URL: const targetUrl = "https://www.eventbrite.com/d/united-states/technology/"; const industryFilter = "?q=artificial+intelligence"; Adjust Networking Priorities: // In Speaker Intelligence node, modify scoring weights: const priorityWeights = { executive_level: 0.4, company_size: 0.3, industry_relevance: 0.2, speaking_topic: 0.1 }; Customize Output Format: // In Networking Strategy node, modify output structure: const outputFormat = { high_priority: speakers.filter(s => s.score > 8), medium_priority: speakers.filter(s => s.score > 6 && s.score <= 8), networking_plan: generateApproachStrategy(speakers) }; Data Storage & Output Formats Storage Options Local JSON files** - Default storage for conference data Google Drive** - For sharing reports with team Database** - PostgreSQL/MySQL for enterprise deployments Cloud Storage** - AWS S3, Google Cloud Storage Output Formats JSON** - Raw data for API integration CSV** - For spreadsheet analysis PDF Reports** - Executive summaries Markdown** - Documentation and sharing Sample Output Structure { "conference_data": { "event_name": "AI Summit 2024", "date": "2024-06-15", "location": "San Francisco, CA", "speakers": [ { "name": "Dr. Sarah Chen", "title": "CTO, TechCorp", "company": "TechCorp Inc", "networking_score": 9.2, "priority": "high", "approach_strategy": "Connect via LinkedIn, mention shared AI interests" } ], "networking_plan": { "high_priority_targets": 5, "recommended_approach": "Focus on AI ethics panel speakers", "schedule_optimization": "Attend morning keynotes, network during breaks" } } } Key Features Automated Conference Discovery** - Finds relevant industry events from multiple sources Speaker Intelligence Analysis** - Identifies high-value networking targets with contact priority scoring Strategic Agenda Mapping** - Optimizes your conference schedule for maximum networking impact AI-Powered Recommendations** - Provides personalized networking strategies and approach methods Priority Contact Lists** - Ranks speakers by business value and networking potential Troubleshooting Common Issues ScrapeGraphAI Rate Limits - Implement delays between requests Website Structure Changes - Update scraping prompts in ScrapeGraphAI nodes API Authentication - Verify credentials and permissions Performance Optimization Adjust trigger frequency based on conference season Implement caching for repeated data Use batch processing for large conference lists Support & Customization For advanced customization or enterprise deployments, consider: Custom speaker scoring algorithms Integration with CRM systems (Salesforce, HubSpot) Advanced analytics and reporting dashboards Multi-language support for international conferences. An n8n automation workflow template by vinci-king-01.

By vinci-king-01

Enterprise Knowledge Search with GPT-4 Turbo, Google Drive & Academic APIs This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. How it works This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. Key Steps Form Input - Collects user queries with customizable search scope, response style, and language preferences Intelligent Search - Routes queries to appropriate sources (web, academic papers, news, internal documents) Data Aggregation - Unifies and processes information from multiple sources with quality scoring AI Processing - Uses GPT-4 Turbo to generate context-aware, source-grounded responses Response Enhancement - Formats outputs in various styles (comprehensive, concise, technical, etc.) Multi-Channel Delivery - Delivers results via webhook, email, Slack, and optional PDF generation Data Sources & AI Models Search Sources Web Search**: Google, Bing, DuckDuckGo integration Academic Papers**: arXiv, PubMed, Google Scholar via Crossref API News Articles**: News API, RSS feeds, real-time news Technical Documentation**: GitHub, Stack Overflow, documentation sites Internal Knowledge**: Google Drive, Confluence, Notion integration AI Models GPT-4 Turbo**: Primary language model for response generation Embedding Models**: For semantic search and similarity matching Custom Prompts**: Specialized prompts for different response styles Set up steps Setup time: 15-20 minutes Configure API credentials - Set up OpenAI API, News API, Google Drive, and other service credentials Set up search sources - Configure academic databases, news APIs, and internal knowledge sources Connect analytics - Link Google Sheets for usage tracking and performance monitoring Configure notifications - Set up Slack channels and email templates for automated alerts Test the workflow - Run sample queries to verify all components are working correctly Keep detailed configuration notes in sticky notes inside your workflow. An n8n automation workflow template by vinci-king-01.

By vinci-king-01

AI-Powered Stock Tracker with Yahoo Finance & Google Sheets ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This automated workflow monitors stock prices by scraping real-time data from Yahoo Finance. It uses a scheduled trigger to run at specified intervals, extracts key stock metrics using AI-powered extraction, formats the data through a custom code node, and automatically saves the structured information to Google Sheets for tracking and analysis. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or cloud) ScrapeGraphAI community node installed Google Sheets API access Yahoo Finance access (no API key required) Required Credentials ScrapeGraphAI API Key** - For web scraping capabilities Google Sheets OAuth2** - For spreadsheet integration Google Sheets Setup Create a Google Sheets document with the following column structure: | Column A | Column B | Column C | Column D | Column E | Column F | Column G | |----------|----------|----------|----------|----------|----------|----------| | symbol | current_price | change | change_percent | volume | market_cap | timestamp | | AAPL | 225.50 | +2.15 | +0.96% | 45,234,567 | 3.45T | 2024-01-15 14:30:00 | How it works This automated workflow monitors stock prices by scraping real-time data from Yahoo Finance. It uses a scheduled trigger to run at specified intervals, extracts key stock metrics using AI-powered extraction, formats the data through a custom code node, and automatically saves the structured information to Google Sheets for tracking and analysis. Key Steps: Scheduled Trigger**: Runs automatically at specified intervals to collect fresh stock data AI-Powered Scraping**: Uses ScrapeGraphAI to intelligently extract stock information (symbol, current price, price change, change percentage, volume, and market cap) from Yahoo Finance Data Processing**: Formats extracted data through a custom Code node for optimal spreadsheet compatibility and handles both single and multiple stock formats Automated Storage**: Saves all stock data to Google Sheets with proper column mapping for easy filtering, analysis, and historical tracking Set up steps Setup Time: 5-10 minutes Configure Credentials: Set up your ScrapeGraphAI API key and Google Sheets OAuth2 credentials Customize Target: Update the website URL in the ScrapeGraphAI node to your desired stock symbol (currently set to AAPL) Configure Schedule: Set your preferred trigger frequency (daily, hourly, etc.) for stock price monitoring Map Spreadsheet: Connect to your Google Sheets document and configure column mapping for the stock data fields Node Descriptions Core Workflow Nodes: Schedule Trigger** - Initiates the workflow at specified intervals Yahoo Finance Stock Scraper** - Extracts real-time stock data using ScrapeGraphAI Stock Data Formatter** - Processes and formats extracted data for spreadsheet compatibility Google Sheets Stock Logger** - Saves formatted stock data to your spreadsheet Data Flow: Trigger → Scraper → Formatter → Logger Customization Examples Track Multiple Stocks // In the ScrapeGraphAI node, modify the URL to track different stocks: const stockSymbols = ['AAPL', 'GOOGL', 'MSFT', 'TSLA']; const baseUrl = 'https://finance.yahoo.com/quote/'; Add Additional Data Fields // In the Code node, extend the data structure: const extendedData = { ...stockData, pe_ratio: extractedData.pe_ratio, dividend_yield: extractedData.dividend_yield, day_range: extractedData.day_range }; Custom Scheduling // Modify the Schedule Trigger for different frequencies: // Daily at 9:30 AM (market open): "0 30 9 * * *" // Every 15 minutes during market hours: "0 */15 9-16 * * 1-5" // Weekly on Monday: "0 0 9 * * 1" Data Output Format The workflow outputs structured JSON data with the following fields: { "symbol": "AAPL", "current_price": "225.50", "change": "+2.15", "change_percent": "+0.96%", "volume": "45,234,567", "market_cap": "3.45T", "timestamp": "2024-01-15T14:30:00Z" } Troubleshooting Common Issues ScrapeGraphAI Rate Limits - Implement delays between requests Yahoo Finance Structure Changes - Update scraping prompts Google Sheets Permission Errors - Verify OAuth2 credentials and document permissions Performance Tips Use appropriate trigger intervals (avoid excessive scraping) Implement error handling for network issues Consider data validation before saving to sheets Pro Tips: Keep detailed configuration notes in the sticky notes within the workflow Test with a single stock first before scaling to multiple stocks Consider modifying the Code node to handle different stock symbols or add additional data fields Perfect for building a historical database of stock performance over time Can be extended to track multiple stocks by modifying the ScrapeGraphAI prompt. An n8n automation workflow template by vinci-king-01.

By Marth - Business Automation

How It Works ⚙️ Imagine a dedicated financial expert tirelessly working behind the scenes, sifting through every transaction, every investment move, and every accounting entry. That's exactly what this automated system does for you, turning raw financial chaos into crystal-clear insights. Automated Data Gathering (The Collector): What happens: The system automatically connects to your bank accounts, investment platforms, and accounting software (like QuickBooks or Xero) on a schedule you define (e.g., daily, weekly). It pulls in all your latest financial data – every transaction, income, expense, and investment update. Data In: Transaction descriptions, amounts, dates, investment details, income/expense categories (if available). AI-Powered Data Cleaning & Categorization (The Organizer & Detective): What happens: Once collected, the data is sent to our first two AI brains. AI Agent 1 (The Categorizer): Reads through every transaction description and intelligently assigns it to a standard financial category (e.g., "Dining," "Groceries," "Utilities," "Software Subscriptions"). No more manual tagging! AI Agent 2 (The Anomaly Detector): Scans the categorized data for anything unusual – a transaction amount that's too high, a potential duplicate entry, or any suspicious activity. It flags these items immediately. Data Out: Clean, categorized transactions, flagged anomalies with reasons. Deep Financial Analysis & Insight Generation (The Strategist): What happens: With clean data in hand, specialized AI agents get to work on the strategic analysis: AI Agent 3 (Spending Pattern Analyst): Identifies your key spending trends over time. Are you spending more on certain categories? Where can you save? AI Agent 4 (Investment Performance Insight): Reviews your investment gains and losses and gives you a clear picture of your portfolio's health. AI Agent 5 (Overall Financial Health Assessor & Recommender): This top-tier AI synthesizes ALL the insights. It provides a concise summary of your overall financial health and, critically, gives you 3-5 clear, actionable recommendations on how to improve your finances or capitalize on opportunities. Data Out: Analysis summaries, spending insights, investment performance notes, overall financial health assessment, and precise recommendations. Automated Reporting & Smart Alerts (The Communicator): What happens: All the AI-generated insights are automatically compiled into a professional financial report. This report populates a pre-designed Google Docs template, making it look polished and ready for review. Immediate Alerts: If AI Agent 2 flagged any anomalies, you get an instant notification (e.g., via Slack) so you can investigate immediately. Report Delivery: The full report is automatically sent to your email inbox, and a summary notification is sent to your team's Slack channel. Outcome: You receive regular, detailed, and actionable financial reports without lifting a finger, always staying informed and ahead. Setup Steps 🛠️ Building this powerful system is simpler than you might think. Here’s your step-by-step guide: Prepare Your Digital Foundation: Financial Data Access: Figure out how you'll get your raw data. For APIs (Recommended): If your bank, investment platform, or accounting software has an API (like Plaid, QuickBooks, Xero), get your API keys and understand their basic HTTP Request structure. For CSVs: If you download CSV statements, ensure they have consistent formats (Date, Description, Amount at minimum). You'll use CSV Read nodes instead of HTTP Request. Google Sheets Database: Create two separate Google Sheets in your Google Drive: "Raw Financial Data" Sheet: This sheet will store all the untouched data collected from your sources. Set up columns like Date, Description, Amount, Source, Transaction Type, Asset, etc. "Categorized Financial Data" Sheet: This sheet will store the data after it's been cleaned and categorized by the AI. Add columns for Category, Is Flagged, Flag Reason, alongside the raw data columns. Financial Report Template (Google Docs): Create a new Google Doc that will be your professional report template. Design it how you want your final report to look. Insert clear placeholders like {{ report_title }}, {{ executive_summary }}, {{ spending_analysis }}, {{ overall_assessment_recommendations }}, etc., where the AI content will go. Crucially, copy the Document ID from the URL of this template. Get Your API Keys & Credentials: OpenAI API Key: This is essential for all the AI brains. Get it from your OpenAI account. Google Sheets Credentials: You'll need to create an OAuth2 credential in n8n to link to your Google Sheets. Gmail Credentials: For sending the final reports. Set up an OAuth2 credential. Slack Credentials: If you want alerts and notifications. Get a Bot Token from your Slack app settings. (Optional) Other API Keys: If you're using specific financial APIs (e.g., Plaid, QuickBooks), gather their respective API keys and authentication details. Import the n8n Workflow: We've provided the detailed node structure in previous responses. You'll translate that into an n8n workflow by adding each node manually and connecting them as described. This gives you full control and understanding! Connect Your Tools (N8n Credentialing & Linking): Go to each node in your n8n workflow that requires a credential (e.g., OpenAI, Google Sheets, Gmail, Slack, HTTP Request). Select the credential you created in Step 2. This links n8n to your external services. Customize Your Workflow Nodes (The Smart Part!): Cron Node (Node 1): Set your desired Schedule (e.g., "Every 1 Day" for daily reports, or "Every 1 Week" for weekly). HTTP Request Nodes (Nodes 2, 3, 4): Paste the exact URLs for your financial APIs. Configure the Method (GET/POST) and Authentication type (e.g., "Header Auth," "OAuth2") specific to each API. If using CSVs: Replace these nodes with CSV Read nodes and point them to your CSV file paths. Google Sheets Nodes (Nodes 7, 8, 13, 14): Paste the Spreadsheet IDs for your "Raw Financial Data" and "Categorized Financial Data" sheets. Ensure the Sheet Name is correct (e.g., "Sheet1" or "Transactions"). Crucially, map the Values correctly so that the data goes into the right columns in your sheets. OpenAI Nodes (Nodes 10, 11, 16, 17, 18): This is the most powerful part! Carefully review and refine the Prompts within these nodes. Tailor the categories for AI Agent 1, specify what counts as an "anomaly" for AI Agent 2, and ensure the tone and focus of recommendations from AI Agent 5 match your needs. Test these prompts extensively! Google Docs Node (Node 20): Paste your Template Document ID from Step 1. Map the Values from your consolidated AI insights ({{ $json.report_title }}, etc.) to the placeholders you created in your Google Doc template. Slack Nodes (Nodes 22, 24): Enter the specific Chat IDs (channel IDs) for where you want anomaly alerts and general report notifications to appear. Test & Activate! Run Manual Tests: Before activating, manually trigger the workflow a few times. Check each node's output to ensure data is flowing correctly and AI agents are generating the expected results. Activate: Once you're confident everything is working, click the "Inactive" toggle in the top-right corner of your workflow to set it live. Congratulations! You've just built a sophisticated, AI-powered financial analysis and reporting system that will bring unprecedented clarity and control to your finances. An n8n automation workflow template by Marth - Business Automation.

By Aitor | 1Node

This n8n automation connects your Google Sheets to Vapi, enabling you to automatically call new contacts as soon as their information is added to your spreadsheet. Instantly reach out with a personalized voice call from a Vapi AI assistant, based on any event that adds a new row to your sheet. 🧾 Requirements Google Sheets Google Sheets credentials** enabled and tested in n8n. A table in your Google Sheet formatted as follows: Required Columns & Data Types | Column Name | Example Value | Data Type | Notes | |---------------|----------------|-------------------|-----------------------------------------------| | phone_number | +11234567890 | Text (String) | Must include the + and country code, no spaces or dashes. Mandatory for workflow. | | (optional) | first_name | John | Text (String) | For call personalization. | | (optional) | email | test@email.com | Text (String) | For follow-ups or records. | | (additional)| Any extra info | | | Can be used for advanced customization. | Ensure all columns contain data in plain text format. Phone number field must never be empty and follow the E.164 international format: + + country code + phone number. Vapi A Vapi account with credit. A connected phone number (to originate calls). An assistant (AI voice agent) created and ready to make calls. Your Vapi API key. 🔗 Useful Link Vapi Docs 🛠️ Comprehensive Setup Instructions 1. Prepare Your Google Sheet Create a Google Sheet with the required column names as listed above. Ensure your phone_number column is correctly formatted (international format, no spaces). Optionally, add columns such as first_name, email, or any field your workflow should use. 2. Set Up Google Sheets Credentials in n8n In n8n, go to "Credentials" and create Google Sheets credentials. Authenticate with your Google account and test the connection. 3. Configure the n8n Workflow Add a Google Sheets Trigger node: Set trigger mode to "New Row". Select your Google Sheet and worksheet. Add a Wait node: Configure a wait time (e.g., 4 minutes) between trigger and next action. 4. Map & Set Vapi Fields Add a Set node: Create fields required by the Vapi API: phone_number_id: Copy from your Vapi dashboard. assistant_id: Use the ID of your AI assistant. api_key: Store securely (see n8n secret management). to: Set as the Google Sheet's phone_number value. Example: {{ $json["phone_number"] }} (Optional) Map extra fields from Sheet (e.g., first_name, email) for personalized calls. 5. Add the HTTP Request to Vapi Add an HTTP Request node: Method: POST URL: https://api.vapi.ai/call Body parameters: Use all mapped fields from previous step. 6. Test the Workflow Add a new row to your Google Sheet. Verify that, after the wait period, Vapi attempts the call and uses personalized information. 🎨 Customization Options Personalize Calls Further:** Add additional columns like first_name, product, or appointment_time in Google Sheets. Map these into the API call so Vapi can use them for dynamic greetings or contextual responses. Conditional Flows:** Insert n8n logic nodes (IF, Switch) before making the Vapi call. For example, only call if a "Consent" column is TRUE, or select different assistants based on region or product interest. Multiple Assistants/Numbers:** Store different assistant IDs or phone number IDs in columns, and dynamically route calls based on sheet data (e.g., region-specific assistants). Advanced Field Mapping:** Pass any relevant sheet fields into the API payload and configure your Vapi assistant scripts to utilize these variables for high-touch, customized user interactions. 📇 Example Google Sheet Setup | phone_number | first_name | email | product | consent | |--------------|------------|------------------|------------|---------| | +11234567890 | John | j@email.com | Widget A | TRUE | | +44207123456 | Maria | maria@x.co.uk | Widget B | FALSE | In n8n, map only those rows where consent=TRUE. 🙋‍♂️ Need Help? Feel free to contact us at 1 Node Get instant access to a library of free resources we created. An n8n automation workflow template by Aitor | 1Node.

By Tushar Mishra

1. Data Ingestion Workflow (Left Panel – Pink Section) This part collects data from the ServiceNow Knowledge Article table, processes it into embeddings, and stores it in Qdrant. Steps: Trigger: When clicking ‘Execute workflow’ The workflow starts manually when you click Execute workflow in n8n. Get Many Table Records Fetches multiple records from the ServiceNow Knowledge Article table. Each record typically contains knowledge article content that needs to be indexed. Default Data Loader Takes the fetched data and structures it into a format suitable for text splitting and embedding generation. Recursive Character Text Splitter Splits large text (e.g., long knowledge articles) into smaller, manageable chunks for embeddings. This step ensures that each text chunk can be properly processed by the embedding model. Embeddings OpenAI Uses OpenAI’s Embeddings API to convert each text chunk into a high-dimensional vector representation. These embeddings are essential for semantic search in the vector database. Qdrant Vector Store Stores the generated embeddings along with metadata (e.g., article ID, title) in the Qdrant vector database. This database will later be used for similarity searches during chatbot interactions. 2. RAG Chatbot Workflow (Right Panel – Green Section) This section powers the Retrieval-Augmented Generation (RAG) chatbot that retrieves relevant information from Qdrant and responds intelligently. Steps: Trigger: When chat message received Starts when a user sends a chat message to the system. AI Agent Acts as the orchestrator, combining memory, tools, and LLM reasoning. Connects to the OpenAI Chat Model and Qdrant Vector Store. OpenAI Chat Model Processes user messages and generates responses, enriched with context retrieved from Qdrant. Simple Memory Stores conversational history or context to ensure continuity in multi-turn conversations. Qdrant Vector Store1 Performs a similarity search on stored embeddings using the user’s query. Retrieves the most relevant knowledge article chunks for the chatbot. Embeddings OpenAI Converts user query into embeddings for vector search in Qdrant. An n8n automation workflow template by Tushar Mishra.

By NAZIA AI ACADEMY

How it works This workflow lets users generate AI images directly from Telegram messages using: Google Gemini API – to convert text to detailed, high-quality image prompts. Pollinations API – to generate free AI images from the prompts. Telegram Bot – to interact with users and return generated images instantly. It’s fully automated using n8n — from text message to stunning image, all in one flow. Perfect for creators, content marketers, or anyone wanting quick visuals on the go. Set up steps 🧩 Estimated setup time: ~10–15 minutes Create a Telegram Bot via @BotFather, copy your token, and set up the Telegram Trigger node in n8n with your credentials. Set up Google Gemini API via Google AI Studio or Cloud Console. Make sure your API key is added in the credentials section of the Gemini node. Customize prompt structure or image size in the Fields - Set Values or Prompt Agent node. (Optional) Enable Save to Disk if you want to keep a local copy of every image. Deploy and run the workflow — done 🎉 🛠️ All technical details and logic are fully documented inside the workflow using sticky notes. ⚠️ Requirements n8n (Self-hosted or Cloud) Telegram Bot Token Google Gemini API key (with billing enabled — includes some free usage) No key needed for Pollinations API — it's 100% free 🆓. An n8n automation workflow template by NAZIA AI ACADEMY.

By David Ashby

🤖 Asana AI Assistant: Project Management via Natural Language Transform chat conversations into Asana actions - This workflow creates an AI agent that lets users manage Asana through conversational commands instead of manual clicks. Key Use Cases: ✅ Accelerated Project Creation → "Create 'Q3 Campaign' project in Marketing workspace with Design team" → Generates projects with correct teams/workspaces in 1 request ✅ Dynamic Task Management → "Add 'Finalize assets' subtask to TSK-123" → "Update 'Blog Post' due date to Friday" → Modifies tasks/subtasks without searching ✅ Automated Reporting → "Show open tasks in Product Launch" → "List last 5 projects in Design workspace" → Pulls live data via conversational queries ✅ Collaboration Boost → "Add comment to TSK-456: Client approved visuals" → Posts context-rich updates while multitasking Ideal For: Managers creating projects during calls Teams updating tasks via Slack/chat PMs generating quick status reports Reducing Asana onboarding friction. An n8n automation workflow template by David Ashby.

By Andrew

Who is this for This workflow is designed for marketers, researchers, and business owners who need to quickly find and export company data from Google Maps into a structured table format. What problem is this workflow solving Manually collecting business contact information from Google Maps is time-consuming and error-prone. This workflow automates the process, allowing users to instantly extract company data and export it to Excel or Google Sheets for further use. For example, title, rating, reviews, address, operating hours, phone, website, type, gps coordinates. What this workflow does Takes a user’s search query via chat Scrapes company data from Google Maps based on that query Returns the results in a downloadable Excel file Saves the same data to a connected Google Sheets document for easy access and sharing Setup Add your credentials: Google Sheets API Google Maps API Run the workflow and enter your search request in the chat interface Retrieve your results from either: The Get XLSX node as an Excel file The linked Google Sheets file. An n8n automation workflow template by Andrew.

By WeblineIndia

Detect duplicate candidates by email/phone from Gmail to Slack using Google Sheets This workflow automatically detects duplicate job applicants by checking incoming emails from Gmail against existing records in Google Sheets. If a candidate's email is already found in the sheet, it sends an alert to Slack; otherwise, it adds the candidate to the sheet. Who’s it for HR and recruitment teams processing candidate emails manually Startups or SMEs handling job applications via Gmail Anyone who wants to automate resume collection and deduplication Teams using Slack and Google Workspace How it works Triggers every few minutes via the Schedule Trigger node Fetches recent emails labeled "applicant" from Gmail Extracts candidate details from the email body using regex Reads all existing rows from the Google Sheet Compares the candidate’s email with existing entries If duplicate → Sends a Slack alert If new → Appends to the Google Sheet How to set up Label candidate emails in Gmail with a label like applicant Connect Gmail, Google Sheets, and Slack credentials in n8n Create a Google Sheet with these columns: candidate_name, candidate_email, candidate_phone, role_applied, years_of_experience, recruiter, resume_url, source_email Import the workflow JSON Update: Gmail label ID Google Sheet ID Slack channel or user Activate the workflow Requirements n8n (self-hosted or cloud) Gmail account with access to labeled application emails Google Sheet to store candidates Slack account with chat:write scope Basic regex familiarity (optional) How to customize Change comparison logic to include phone numbers. Add fallback logic to check for similar names. Add filters for roles, experience levels. Forward resumes to Drive or Notion. Trigger an approval flow for screened candidates. Add‑ons Google Drive: Upload parsed resumes. Notion / Airtable: Store structured candidate records. Webhooks: Forward to ATS or CRM. PDF parsers: Extract data from attachments. Use Case Examples | Use Case | Description | | ------------------- | ----------------------------------------------------- | | Resume deduplication | Avoid processing the same applicant twice | | Auto Slack alert | Instantly notify recruiter of repeat candidates | | Centralized tracking | Keep candidate records in Sheets for filtering/export | | Passive sourcing | Run hourly checks on labeled Gmail inboxes | Common troubleshooting | Issue | Possible Cause | Solution | | ------------------------ | ------------------------------------------ | -------------------------------------------------------------- | | Slack message not sent | Invalid Slack token / channel not selected | Reauthorize Slack connection and select correct user/channel | | Google Sheet not updated | Sheet ID or tab name is incorrect | Double-check the Sheet URL and worksheet tab | | Email data not extracted | Email body format doesn’t match regex | Adjust regex in the "Code" node | | Nothing happens | Gmail label or date filter is too strict | Ensure emails exist with the right label in the last X minutes | Need Help? Need help setting it up or tweaking regex for your custom email format? We’re happy to help — just ask! Want to add phone number duplication checks or auto-resume upload to Google Drive? Our Automation team at WeblineIndia can guide you step-by-step. An n8n automation workflow template by WeblineIndia.

By Intuz

This n8n template from Intuz provides a complete and automated solution for scaling your DevOps practices across multiple repositories. Are you tired of the repetitive dance between git push, creating a pull request in GitHub, updating the corresponding task in JIRA, and then manually notifying your team in Slack, or Notion? This template puts your entire post-commit workflow on autopilot, creating a seamless and intelligent bridge between your code and your project management. By embedding specific keywords and a JIRA issue ID into your git commit commands, this workflow automatically creates a Pull Request in the correct GitHub repository and updates the corresponding JIRA ticket. This creates a complete, centralized system that keeps all your projects synchronized, providing a massive efficiency boost for teams managing a diverse portfolio of codebases. Who This Template Is For? This template is a must-have for any organization looking to streamline its software development lifecycle (SDLC). It’s perfect for: Development Teams: Eliminate tedious, manual tasks and enforce a consistent workflow, allowing developers to stay focused on coding. DevOps Engineers: A ready-to-deploy solution that integrates key developer tools without weeks of custom scripting. Engineering Managers & Team Leads: Gain real-time visibility into development progress and ensure processes are followed without constant check-ins. Project Managers: Get accurate, automatic updates in JIRA the moment development work is completed, improving project tracking and forecasting. Step-by-Step Setup Instructions Follow these steps carefully to configure the workflow for your environment. 1. Connect Your Tools (Credentials) GitHub: Create credentials with repo scope to allow PR creation. JIRA: Create an API token and connect your JIRA Cloud or Server instance. Slack: Connect your Slack workspace using OAuth2. Notion: Connect your Notion integration token. 2. Configure the GitHub Webhook (For Each Repository) This workflow is triggered by a GitHub webhook. You must add it to every repository you want to automate. First, Save and Activate the n8n workflow to ensure the webhook URL is live. In the n8n workflow, copy the Production URL from the Webhook node. Go to your GitHub repository and navigate to Settings > Webhooks > Add webhook. In the Payload URL field, paste the n8n webhook URL. Change the Content type to application/json. Under "Which events would you like to trigger this webhook?", select "Just the push event." Click "Add webhook." Repeat this for all relevant repositories. 3. Configure the JIRA Nodes (Crucial Step) Your JIRA project has unique IDs for its statuses. You must update the workflow to match yours. Find the two JIRA nodes named "Update task status after PR" and "Update the task status without PR." In each node, go to the Status ID field. Click the dropdown and select the status that corresponds to "Done" or "Development Done" in your specific JIRA project workflow. The list is fetched directly from your connected JIRA instance. 4. Configure Notification Nodes Tell the workflow where to send updates. For Slack: Open the two nodes named "Send message in slack..." and select your desired channel from the Channel ID dropdown. For Notion: Open the two nodes named "Append a block in notion..." and paste the URL of the target Notion page or database into the Block ID field. 5. Final Activation Once all configurations are complete, ensure the workflow is Saved and the toggle switch is set to Active. You are now ready to automate! Customization Guidance This template is a powerful foundation. Here’s how you can adapt it to your team's specific needs. 1. Changing the PR Title or Body: Go to the "Request to create PR" (HTTP Request) node. In the JSON Body field, you can edit the title and body expressions. For example, you could add the committer's name ({{$('Webhook').item.json.body.pusher.name }}) or a link back to the JIRA task. 2. Adapting to a Fixed Branching Strategy: If your team always creates pull requests against a single branch (e.g., develop), you can simplify the workflow. In the "Request to create PR" node, change the base value in the JSON body from {{...}} to your static branch name: "base": "develop". You can then remove the base branch logic from the "Commit Message Breakdown" (Code) node. 3. Modifying Notification Messages: The text sent to Slack and Notion is fully customizable. Open any of the Slack or Notion nodes and edit the text fields. You can include any data from previous nodes, such as the PR URL ({{ $('Request to create PR').item.json.body.html_url }}) or the repository name. 4. Adjusting the Commit Regex for Different Conventions: This is an advanced customization. If your team uses a different commit format (e.g., (DEV-123) instead of DEV-123), you can edit the regular expression in the "Commit Message Breakdown" (Code) node. Be sure to test your changes carefully. 5. Adding/Removing Notification Channels: Don't use Notion? Simply delete the two Notion nodes. Want to send an email instead? Add a Gmail or SMTP node in parallel with a Slack node and configure it with the same data. Connect with us Website: https://www.intuz.com/n8n-workflow-automation-templates Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started. An n8n automation workflow template by Intuz.

By Michael Taleb

How it works Watches a Google Drive folder for new (scanned) invoices. Each new file automatically triggers the workflow. Downloads and processes each invoice through OCR Space to extract the text. Extracts the company name (e.g. from the “billed to” field) and uses an AI agent to cross-reference it against a database in Google Sheets. If a match is found, retrieves the correct recipient email and sends the invoice as an attachment. If no match or an error occurs, the workflow alerts an operator by email for manual review. Setting up the workflow Connect Google Drive • In n8n, connect your Google Drive account. • Create or select a folder where you will upload scanned invoices. Connect Gmail (or another email service) • Add your Gmail account as a credential in n8n. • This will be used to send the processed invoice to the correct recipient. Set up OCR.Space • Create a free OCR.Space account: https://ocr.space • In n8n, create a Generic Credential (Header Auth). • Use apikey as the name and your OCR API key as the value. Connect the AI Agent • Add your OpenAI API key as a credential in n8n. • The AI Agent will extract the company name from the invoice text and match it against your database. • If a match is found, it retrieves the correct email. Prepare the Google Sheet database • Make a copy of the database sheet: Google Sheet Template • Fill it with company names and recipient emails. • Connect your Google account to n8n and link this sheet to the workflow. Run the workflow • When a new invoice is uploaded to your Google Drive folder, the workflow will: • Extract the text with OCR.Space • Use the AI Agent to identify the company name • Cross-reference it with your Google Sheet database • Send the invoice automatically to the correct recipient via Gmail • If no match is found, an error email is sent to you for manual review. An n8n automation workflow template by Michael Taleb.

By Hybroht

URL Officer - Respect robots.txt and Avoid Undesirable Sources 🎬 Overview Version : 1.0 The URL Officer workflow automates the filtering of URLs by checking them against a database of forbidden sources and the rules defined in robots.txt files. It proactively respects robot exclusion protocols and user-defined banned sources to aid in lawful and ethical web automation. Designed primarily as a sub-workflow, it serves automation pipelines with robust URL validation to avoid undesirable or restricted sources. ✨ Features Dual-layer URL Filtering**: Checks URLs against a manually maintained forbidden sources list and robots.txt restrictions. Automated robots.txt Retrieval & Update**: Automatically fetches and updates robots.txt content for new or outdated sources (older than 3 days). AI-backed robots.txt Interpretation**: Uses AI models to interpret robots.txt comments and restrictions, ensuring nuanced compliance. Configurable User-Agent Identification**: Allows customization of User-Agent strings that are checked against robots.txt directives. Sub-Workflow Ready**: Easily integrates as a sub-workflow for link validation in larger automation pipelines. Multi-Model AI Support**: Supports mistral, groq, and gemini AI models for enhanced robots.txt compliance checks. Detailed Diagnostic Outputs**: Returns comprehensive link allowance statuses and metadata for use in downstream processing. Database Integration**: Utilizes PostgreSQL to store and manage robots.txt content and banned source lists. 👤 Who is this for? Ideal for developers, data engineers, researchers, or businesses implementing web crawlers, scrapers, or any automation that processes URLs. This workflow helps your compliance with source restrictions and avoids content from blacklisted sites, reducing legal exposure and promoting ethical data use. 💡 What problem does this solve? URL Officer addresses the challenge of automating URL validation by combining manual blacklist filtering with automated and AI-assisted robots.txt parsing. It prevents accidental scraping or processing from undesirable or disallowed sources, helping automate respect for webmasters' policies and legal boundaries. 🔍 What this workflow does When given a URL, the workflow: Extracts the base URL. Checks the URL against a manually configured banned sources list (stored in database). Fetches robots.txt for new or stale sources (older than 3 days). Performs a programmatic parse and check of robots.txt directives against the URL using the specified User-Agent. Runs an AI model to analyze robots.txt content and confirm if the URL is allowed, taking into account any special comments or prohibitions relevant to the automation goal. Returns a final "allow or disallow" determination for both the URL and its base URL, along with metadata about the robots.txt fetch status and timing. 🔄 Workflow Steps 1. Input Parsing & Base URL Extraction Accepts workflow arguments including the URL, User-Agent information, automation goal, and AI model choice. Extracts and normalizes the base URL for processing. 2. Forbidden Source Check Queries PostgreSQL tables containing banned sources. Immediately rejects URLs matching forbidden sources. 3. robots.txt Handling Checks if robots.txt content for the source is in the database and is recent (under 3 days old). If missing or outdated, fetches the robots.txt file from the base URL and updates the database. 4. Code-Based robots.txt Analysis Parses robots.txt directives, matching the User-Agent to appropriate groups. Checks if the URL and base URL paths are allowed according to the parsed rules. Uses a conservative URL and agent matching algorithm for prefix-based allow/disallow checks. 5. AI-Based robots.txt Verification Uses the selected AI model (mistral, groq, or gemini) to analyze robots.txt content and comments regarding allowed automation use. Applies AI understanding to confirm or override automated code checks based on the automation's goal. 6. Output Preparation Produces output indicating permission statuses (allow_link and allow_baseUrl), original URLs, User-Agent info, fetch timestamps, and whether robots.txt was successfully retrieved. Designed to be consumed by other workflows as a validation step. 🔀 Expected Input / Configuration The workflow is configured primarily via workflow input arguments: | Parameter | Description | Type | |-------------------|---------------------------------------------------------------------------------------------------|---------| | link | The URL to be checked. | String | | userAgent | User-Agent string representing your automation, used for robots.txt checks. | String | | userAgent_extra | Additional User-Agent information such as version or contact info. | String | | automationGoal | Description of your automation’s purpose, used by the AI to verify suitability against robots.txt. | String | | model | AI model to use for the robots.txt compliance check. Options: mistral, groq, gemini. | String | Database Requirements PostgreSQL database configured with credentials accessible to the workflow. Two tables: one for banned sources (manually maintained) and one for robots.txt content with timestamps. The workflow auto-creates and manages these tables. Recommended to use a containerized PostgreSQL instance (Podman or Docker). 📦 Expected Output A structured JSON object containing: | Output Key | Description | |-----------------|-----------------------------------------------------------------| | link | The URL that was checked. | | baseUrl | The base URL of the checked link. | | allow_link | Boolean indicating if the link is allowed according to checks.| | allow_baseUrl | Boolean indicating if the base URL is allowed. | | userAgent | User-Agent string used in the check. | | userAgent_extra| Additional User-Agent metadata. | | robots_fetched| Boolean, true if robots.txt content was successfully fetched. | | fetched_at | Timestamp of the last robots.txt content fetch. | 📌 Example Example input payload: ⚙️ n8n Setup Used n8n version:** 1.108.2 Platform:** Podman 4.3.1 on Linux PostgreSQL:** Running in Podman 4.3.1 container LLM Models:** mistral-small-latest, llama-3.1-8b-instant (Groq), gemini-2.5-flash Date:** 2025-08-29 ⚡ Requirements to Use / Setup Self-hosted or cloud n8n instance with database connectivity. PostgreSQL database configured and accessible by n8n. Setup PostgreSQL using the recommended containerized deployment or your preferred method. Configure database credentials inside the workflow. Provide API credentials for your chosen AI model (mistral, groq, gemini). Manually maintain the banned sources list in the database. Familiarity with n8n variables and sub-workflow integration is recommended. Internet connectivity for fetching robots.txt files. ⚠️ Notes, Assumptions & Warnings Database tables used by this workflow are automatically created and managed by the workflow. robots.txt refresh interval is set to every 3 days; this can be adjusted by modifying the workflow. The robots.txt parser is relatively simple and does not support wildcard (*) or end-of-string ($) rules. User-Agent matching is substring-based and longer string matches take precedence. AI analysis adds a human-like understanding of robots.txt comments and prohibitions but depends on the quality and capability of the chosen AI model. This workflow does NOT handle: Terms of Service compliance. Preference for official APIs over HTML scraping. Rate-limiting or request throttling. Handling paywalled or restricted content. De-duplication or filtering beyond the banned sources list. Encryption or secure storage. You remain responsible for ensuring your automation complies with legal, ethical, and platform-specific rules. The workflow is designed as a sub-workflow; integrate it into larger automation processes to validate URLs. 🛠 PostgreSQL Setup Instructions (Self-Hosted Route) Available inside the Workflow Notes, alongside podman commands. ℹ️ About Us This workflow was developed by the Hybroht team. Our goal is to create tools that harness the possibilities of technology and more. We aim to continuously improve and expand functionalities based on community feedback and evolving use cases. For questions, support, or feedback, please contact us at: contact@hybroht.com ⚖️ Warranty & Legal Notice This workflow is provided "as-is" without warranties of any kind. By using this workflow, you agree that you are responsible for complying with all applicable laws, regulations, and terms of service related to your data sources and automations. Please review all relevant legal terms and use this workflow responsibly. Hybroht disclaims any liability arising from use or misuse of this workflow. This tool assists with robots.txt compliance but is not a substitute for full legal or compliance advice. You can view the full license terms here. Please review them before making your purchase. By purchasing this product, you agree to these terms. An n8n automation workflow template by Hybroht.

By Issam AGGOUR

AI-Powered Git Changelog Generator for Automated Release Notes This workflow transforms your software release process by automatically generating clean, professional changelogs from your Git commit history. It listens for new version tags in your GitHub repository, uses AI to summarize the changes, and publishes a polished release note, saving you hours of manual work. Disclaimer This template is designed for self-hosted n8n instances and requires API credentials for GitHub and an AI provider (e.g., OpenAI, Google Gemini). 🚀 Key Features Fully Automated Process:** Triggers automatically on a git push --tags event. Set it up once and forget about it. AI-Powered Summarization:** Leverages a Large Language Model (LLM) to intelligently read, categorize, and summarize your commit messages into a human-friendly format. Seamless GitHub Integration:** Fetches commit data and creates official GitHub Releases without leaving the n8n environment. Smart Categorization:** Automatically groups release notes into sections like "Features," "Fixes," and "Other Changes" for clarity. Highly Customizable:** Easily adapt the AI prompt, changelog format, and release template to match your project's style. Saves Developer Time:** Eliminates the tedious, manual task of writing release notes, freeing up developers to focus on coding. ⚙️ How It Works The workflow is a linear process triggered by a webhook from GitHub. 1. GitHub Webhook Trigger A Webhook node is configured to listen for push events from your specified GitHub repository. It is filtered to only run when a new tag (e.g., v1.2.0) is pushed, which is the standard practice for signaling a new release. 2. Fetch Commit History Once triggered, a GitHub node uses the webhook payload to identify the repository and the new tag. It makes an API call to GitHub to compare the new tag with the most recent previous tag, fetching all the commit messages in between. 3. AI Summarization The list of raw commit messages is passed to an AI node (e.g., OpenAI or Google Gemini). A pre-defined prompt instructs the AI to process the commits. The prompt asks the model to summarize the changes and group them into logical categories. The AI returns a single, well-formatted markdown text block representing the complete changelog. 4. GitHub Release Creation The final GitHub node takes the AI-generated markdown. It creates a new GitHub Release, using the tag from the webhook as the release version and the AI-generated text as the release body/description. 🛠️ Setup Steps & Credentials To get this workflow running, you will need to configure the following credentials and settings: GitHub: You need a GitHub Personal Access Token with repo scope to allow n8n to access your repository. Create a GitHub OAuth2 Api or GitHub Api credential in n8n. Assign this credential to the Get Commits and Create GitHub Release nodes. In the Webhook node, copy the Test URL and add it as a new webhook in your GitHub repository's settings (Settings > Webhooks). Set the content type to application/json and select "Just the push event" or "Send me everything," then filter for tag pushes in the workflow itself. AI Provider (OpenAI / Gemini): Obtain an API Key from your chosen AI provider (e.g., platform.openai.com or aistudio.google.com). Create the corresponding credential in n8n (e.g., OpenAI API or Google Gemini(PaLM) Api). Assign this credential to the Generate Changelog with AI node. 💡 Customization & Learning This workflow is a powerful base that you can easily extend: Refine the AI Prompt:** Modify the prompt in the Generate Changelog with AI node to change the tone, language, or structure of your release notes. You could ask it to generate a "What's New" section in a different style, for example. Add Notifications:** Extend the workflow by adding a Discord or Slack node after the final step to notify your team or community channel that a new version has been released. Support Different Git Providers:** Swap the GitHub nodes for GitLab or other provider nodes to adapt the workflow to a different platform. Experiment with Models:** Try different AI models (e.g., GPT-4 vs. GPT-3.5-Turbo, or different Gemini versions) to see how it affects the quality and cost of your generated changelogs. An n8n automation workflow template by Issam AGGOUR.

By Parag Javale

Turn a simple email workflow into a LinkedIn content machine. Generate post ideas, draft full posts, and auto-publish to LinkedIn all controlled by replying to emails. 📌 Purpose Automate your LinkedIn posting pipeline using AI + Email approvals. Generate 10 scroll-stopping post ideas tailored to your niche & audience. Approve your favorite by replying to the email with a number. Receive 3 AI-written drafts for the chosen idea. Pick your favorite draft via email reply. The selected post gets auto-published to LinkedIn ✅. All steps are logged in Google Sheets. 🔗 Apps Used Google Gemini** → generates ideas & drafts Gmail** → email-based approval workflow Google Sheets** → tracks ideas, drafts, and published posts LinkedIn API** → posts directly to your company or personal account ✨ Highlights 📬 Email-based approval → no dashboards, just reply with a number 📝 10 AI-generated content ideas + 3 full drafts per topic 🔄 End-to-end tracking in Google Sheets (ideas → drafts → published) ⚡ Auto-posting directly to LinkedIn ✅ Final confirmation email with preview 👤 Best For Startup founders Agencies managing multiple clients’ LinkedIn Solopreneurs & creators who want consistent posting 🛠️ Workflow Overview flowchart TB A["Manual Trigger"] --> B["AI Agent - Generate 10 Ideas"] B --> C["Code - Parse JSON + Correlation ID"] C --> D["Google Sheets - Append Ideas"] D --> E["Gmail - Send Ideas Email"] E --> F["Gmail Trigger - Await Reply"] F --> G["Code1 - Extract Reply Number"] G --> H["Google Sheets - Fetch Row"] H --> I{"Switch Stage"} I -- Ideas --> J["AI Agent - Generate 3 Drafts"] J --> K["Code3 - Parse Drafts"] K --> L["Google Sheets - Update Drafts"] L --> M["Gmail - Send Drafts Email"] I -- Drafts --> N["Code4 - Select Final Draft"] N --> O["LinkedIn - Publish Post"] O --> P["Google Sheets - Update Posted"] P --> Q["Gmail - Send Confirmation"] `. An n8n automation workflow template by Parag Javale.

By Paul Kobelke

Remove Duplicates & Update Google Sheets How it Works This workflow helps you keep your Google Sheets clean and up-to-date by automatically removing duplicate entries and re-uploading the cleaned data back to your sheet. It’s especially useful for large lead lists, email databases, or any dataset where duplicate rows can cause confusion and inefficiency. The flow: Trigger the workflow manually. Fetch all rows from a specific Google Sheet. Identify and remove duplicate rows based on the profileUrl field. Convert the cleaned dataset into a file. Update the original Google Sheet with the new, deduplicated data. Setup Steps Connect your Google Sheets and Google Drive credentials in n8n. Update the workflow with your desired spreadsheet and sheet ID. Run the workflow by clicking “Execute Workflow” whenever you want to clean up your data. The process only takes a few seconds and ensures your sheet stays organized without any manual effort. Use Cases CRM lead management (avoiding duplicate prospects). Contact lists with scraped or imported data. Marketing databases with overlapping submissions. An n8n automation workflow template by Paul Kobelke.

By Chris Rudy

Who's it for Service businesses that handle installation appointments and need an efficient approval process. Perfect for HVAC companies, internet providers, appliance installers, or any business that requires team coordination before confirming customer appointments. How it works This workflow automates your entire installation booking process from form submission to customer communication. When a customer submits a booking request, your team gets notified via Slack with easy approve/reject buttons. Based on the team's decision, customers automatically receive either a confirmation email with appointment details or a friendly reschedule request with a new booking link. How to set up Connect your accounts: Link your Slack workspace and Gmail account to n8n Configure the Slack channel: Update the SLACK_CHANNEL_ID in the "Set Fields" node with your desired channel Customize your branding: Update COMPANY_NAME, CONTACT_PERSON, and RESCHEDULE_LINK variables Deploy the form: Use the form trigger URL on your website or share it directly with customers Test the workflow: Submit a test booking to ensure everything works smoothly Requirements Active Slack workspace with a designated channel for booking notifications Gmail account for sending automated emails Basic n8n account (free tier works perfectly) How to customize the workflow The workflow is designed for easy customization through the "Set Fields" node. You can modify: Time slots**: Edit the dropdown options in the form trigger Email templates**: Customize confirmation and reschedule email content Slack notifications**: Adjust the message format and approval options Form fields**: Add or remove customer information fields as needed The configuration variables in the "Set Fields" node make it easy to adapt this workflow to your specific business needs without touching the core logic. An n8n automation workflow template by Chris Rudy.

By Chris Rudy

Who's it for Marketing teams, copywriters, and agencies who need to quickly generate and iterate on ad copies for Meta and TikTok campaigns. Perfect for brands that want AI-powered copy generation with human review and approval built into the workflow. What it does This workflow automates the ad copy creation process by: Collecting brand and product information through a form Using AI to generate tailored ad copies based on brand type (Fashion or Problem-Solution) Sending copies to Slack for team review and approval Handling revision requests with feedback incorporation Limiting revisions to 3 rounds to maintain efficiency How to set up Configure your OpenAI credentials in the OpenAI nodes Set up Slack integration and select your review channel in all Slack nodes Customize the AI prompts in the OpenAI nodes to match your brand voice Test the form to ensure file uploads and data collection work properly Activate the workflow when ready Requirements OpenAI API access (GPT-3.5 or GPT-4) Slack workspace with appropriate channel permissions Self-hosted n8n instance (for file upload functionality) How to customize Adjust the AI prompts in OpenAI nodes to match your specific industry or brand guidelines Modify the revision limit in the "Edit Fields: Revision Counter Max 3" node Add additional brand types in the form dropdown and corresponding AI nodes Customize Slack messages to match your team's communication style. An n8n automation workflow template by Chris Rudy.

By Chris Rudy

Who's it for Marketing agencies, digital agencies, and freelancers who need to streamline their client onboarding process and create consistent, professional documentation for new clients. Perfect for teams handling multiple client intakes who want to save hours of manual setup work while maintaining quality standards. What it does This workflow automates the entire client onboarding journey from the moment a prospect fills out your Typeform intake questionnaire. It instantly creates a complete Google Drive folder structure with 6 main folders and 15+ subfolders tailored for marketing projects, sends the intake information to your team via Slack, generates an AI-powered marketing research brief using OpenAI, implements an approval workflow with revision capabilities, and delivers a professional welcome email to the client. The system ensures nothing falls through the cracks while maintaining consistent quality across all client projects. How it works Intake Trigger: When a client submits your Typeform intake form, the workflow automatically initiates Folder Creation: Creates a branded client folder in Google Drive with organized subfolders for ads, raw footage, product images, research, drafts, and archives Team Notification: Posts detailed intake responses to your designated Slack channel for immediate team visibility AI Brief Generation: Uses OpenAI to analyze intake responses and generate a comprehensive marketing research document including customer personas, pain points, positioning strategies, and marketing angles Approval Process: Sends the brief for team review with built-in approve/revise functionality Document Creation: Upon approval, creates a Google Doc with the finalized research brief Client Communication: Sends a personalized welcome email to the client confirming their onboarding How to set up Configure the workflow: Start by filling in all values in the "⚙️ Configuration" node: Your Typeform ID from your intake form Google Drive parent folder ID where client folders will be created Slack channel IDs for new client notifications and internal reviews OpenAI model preference (GPT-4 recommended) Welcome email template with your agency branding Connect your accounts: Typeform: Create credentials and connect your account Google: Authenticate with Drive, Docs, and Gmail permissions Slack: Add the n8n bot to your workspace and relevant channels OpenAI: Add your API key for AI content generation Test the workflow: Submit a test entry through your Typeform Verify folder creation in Google Drive Check Slack notifications are posting correctly Confirm the approval process works as expected Requirements Typeform** account with a client intake form created Google Workspace** account with Drive, Docs, and Gmail access Slack** workspace with appropriate channels created OpenAI API** key with credits for content generation n8n** instance (self-hosted or cloud) version 1.0+ How to customize the workflow Folder Structure**: Modify the subfolder nodes to match your agency's project organization needs Intake Fields**: Update the Slack message blocks and AI prompt to match your specific Typeform fields Research Brief Template**: Customize the OpenAI prompt to generate briefs aligned with your agency's format Approval Logic**: Add additional approval stages or skip approval for certain client types Welcome Email**: Personalize the email template with your branding, links, and next steps Notification Channels**: Route different types of notifications to specific Slack channels based on client tier or project type. An n8n automation workflow template by Chris Rudy.

By Abideen Bello

Generate daily audio newsletters from news headlines with AI Who's it for Perfect for content creators, podcasters, news enthusiasts, and busy professionals who want to create automated audio news content or stay informed through personalized audio briefings. Ideal for social media managers, newsletter creators, and anyone building audio-first content experiences. How it works This workflow creates a fully automated news-to-audio pipeline: Schedule trigger fetches the latest news headlines from NewsAPI daily AI processing rewrites each article into newsletter-style content using Claude Content aggregation combines all processed articles into a cohesive newsletter Script generation transforms the newsletter into a 2-minute audio-ready script Text-to-speech converts the script into high-quality audio using OpenAI's voice models Email delivery sends the audio newsletter as an attachment to subscribers The workflow runs automatically on your chosen schedule, delivering fresh audio content without any manual intervention. How to set up Requirements NewsAPI account** with API key (free tier available) OpenRouter API access** for Claude model OpenAI API account** for text-to-speech functionality Gmail account** with OAuth2 access for email delivery Basic understanding** of audio file handling (optional) Step-by-step setup 1. Set Your Schedule trigger Configure the Schedule Trigger for your preferred timing (daily at 7 AM recommended) Consider your audience timezone and optimal delivery times Set up monitoring to ensure consistent execution 2. Configure News Source Sign up for NewsAPI at newsapi.org (free tier includes 100 requests/day) Replace YOUR_NEWSAPI_KEY with your actual API key in the HTTP Request node Customize the news query parameters (country, category, sources) to match your audience interests Test the API endpoint to ensure it returns expected data 3. Extract Individual Articles(Split Out) Takes the articles array from NewsAPI response Creates separate items for each news article Enables individual processing of each story Prepares data for AI content generation 4. Set Up AI Model Credentials Create an OpenRouter account for Claude access Add your OpenRouter API credentials in n8n Alternatively, replace with OpenAI GPT-4 if you prefer (update the model node accordingly) Configure rate limits and usage monitoring 5. Combine Newsletter Content" (Aggregate) Collects output from all processed articles Renames field to news for easy reference Prepares combined content for script generation Ensures no articles are lost in processing 6. Audio Script Generation GPT-4 creates 2-minute audio-ready script from newsletter content. Creates script with "Max" presenter persona Script features: 2-minute target duration Audio-friendly text (no special characters) Natural speaking flow and transitions Engaging introduction and conclusion 7. Configure OpenAI Text-to-Speech Add your OpenAI API credentials in n8n Choose your preferred voice model (options: alloy, echo, fable, onyx, nova, shimmer) Set audio quality preferences (standard vs HD) Test voice output with sample text 8. Customize Email Delivery Add your Gmail OAuth2 credentials Replace YOUR_EMAIL@example.com with your actual recipient email Update the sender name and business information in email template Configure attachment settings for audio files 9. Test the Complete Pipeline Run a manual execution to test all components Verify news data is properly fetched and processed Check audio quality and duration Confirm email delivery with audio attachment How to customize the workflow Advanced News Filtering Custom sources**: Replace NewsAPI with RSS feeds from specific publications Topic filtering**: Add keyword filtering to focus on specific industries or topics Multi-country support**: Fetch news from multiple regions and merge content Sentiment analysis**: Filter out negative news or categorize by sentiment Trending topics**: Integrate with social media APIs to include trending discussions AI Content Enhancement Voice persona**: Customize the AI prompt to create different presenter personalities (professional, casual, expert) Length control**: Adjust script length for different formats (1-minute updates, 5-minute deep dives) Multi-language support**: Generate newsletters in different languages based on subscriber preferences Fact-checking**: Add verification steps to ensure accuracy of AI-generated content Source attribution**: Include proper citations and links to original articles Audio Production Features Voice variety**: Rotate between different OpenAI voices for engaging content Background music**: Add intro/outro music using audio editing APIs Speed control**: Adjust playback speed based on content type Chapter markers**: Add timestamps for different news segments Quality optimization**: Implement audio normalization and enhancement Distribution Enhancements Multi-channel delivery**: Send to Slack, Discord, or team communication platforms Podcast publishing**: Automatically upload to podcast platforms via RSS Social media**: Post audio clips to Twitter, LinkedIn, or Instagram Website integration**: Embed audio player on your website automatically Mobile app push**: Send notifications to mobile apps with audio links Subscriber Management Mailchimp integration**: Build and manage subscriber lists automatically Preference tracking**: Allow subscribers to choose news categories or frequency Analytics tracking**: Monitor open rates, listening duration, and engagement A/B testing**: Test different voice styles, content lengths, or delivery times Segmentation**: Send different newsletters to different subscriber segments Content Workflow Customization Editorial review**: Add approval steps before content distribution Content calendar**: Integrate with planning tools for scheduled content themes Collaborative editing**: Include team review processes for content quality Version control**: Maintain archives of previous newsletters for reference Performance metrics**: Track which content types perform best Webhook Integration Examples Website Integration // Add this to your website for manual newsletter requests fetch('/webhook/trigger-newsletter', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({ subscriber_email: 'user@example.com', topics: ['technology', 'business'], urgency: 'normal' }) }); Slack Command Integration Create slash commands to trigger newsletter generation on demand Allow team members to request specific topic newsletters Integrate with Slack workflows for automated team briefings Mobile App Integration Use webhooks to trigger newsletters from mobile app interactions Create push notification systems for breaking news alerts Build in-app audio players for seamless listening experience Troubleshooting Common Issues and Solutions NewsAPI quota exceeded: Monitor your daily API usage in NewsAPI dashboard Implement caching to reduce redundant requests Consider upgrading to paid plan for higher limits Add fallback RSS feeds when API limits are reached AI model rate limiting: Implement exponential backoff for API requests Monitor token usage across Claude and OpenAI services Add queue systems for high-volume processing Consider switching to different models during peak times Audio generation failures: Check OpenAI text-to-speech quotas and billing Validate text input for special characters that might cause issues Implement retry logic for failed audio generation Add fallback to text-only newsletters when audio fails Email delivery problems: Verify Gmail API quotas and sending limits Check audio file size limits (Gmail has 25MB attachment limit) Implement compression for large audio files Consider cloud storage links instead of direct attachments Content quality issues: Fine-tune AI prompts for more consistent output Add content validation steps to check for accuracy Implement editorial guidelines in AI instructions Create feedback loops to improve content over time Performance Optimization Workflow efficiency: Process news articles in parallel where possible Implement smart caching for repeated content Optimize API calls to reduce latency Monitor execution times and identify bottlenecks Cost management: Track API costs across all services (NewsAPI, OpenRouter, OpenAI) Implement budget alerts and automatic shutoffs Optimize content length to reduce text-to-speech costs Consider batch processing during off-peak hours Scalability preparation: Design for multiple subscriber support Plan for increased news volume during major events Prepare backup systems for service outages Document processes for team handoffs Security and Compliance API key protection: Never expose API keys in workflow exports Use n8n's credential management exclusively Implement key rotation policies Monitor for unauthorized API usage Content compliance: Review AI-generated content for accuracy and bias Implement content filtering for inappropriate material Ensure proper attribution to original news sources Maintain editorial standards and fact-checking processes. An n8n automation workflow template by Abideen Bello.

By Meelioo

How It Works Monitors Reddit:** Automatically searches specified subreddits for posts matching your keywords or flair filters (template is n8n - Now Hiring flair) AI Analysis:** Processes found posts using AI to create personalized summaries based on your custom prompts Smart Filtering:** Tracks previously sent posts in Google Sheets to avoid duplicate notifications Telegram Delivery:** Sends AI-generated summaries directly to your Telegram chat Set Up Steps Time required: ~15-20 minutes Configure Credentials (10 mins):** Set up Telegram bot token, Reddit app credentials, and Google Sheets access Customize Search Parameters (3 mins):** Define target subreddit, keywords/flairs, and post limits Personalize AI Settings (2 mins):** Adjust AI model and system prompts for your preferred summary style Set Schedule & Chat (2 mins):** Choose monitoring frequency and configure your personal Telegram chat ID >The workflow includes detailed setup instructions and configuration guidance in the sticky notes within the template. An n8n automation workflow template by Meelioo.

By Edoardo Guzzi

Auto-update n8n instance with Coolify Who’s it for This workflow is designed for self-hosted n8n administrators who want to keep their instance automatically updated to the latest stable release. It removes the need for manual version checks and ensures deployments are always up to date. What it does The workflow checks your current n8n version against the latest GitHub release. If a mismatch is detected, it triggers a Coolify deployment to update your instance. If both versions match, the workflow ends safely without action. How it works Trigger: Start manually or on a schedule. HTTP Request (n8n settings): Fetches your current version (versionCli). HTTP Request (GitHub): Fetches the latest n8n release (name). Merge (SQL): Keeps only the two fields needed. Set (Normalize): Converts values into comparable variables. IF Check: Compares current vs latest version. If different → Deploy update. If same → Stop with no operation. HTTP Request (Coolify): Triggers a forced redeploy via API. How to set up Replace https://yourn8ndomain/rest/settings with your own n8n domain. Replace the Coolify API URL with your Coolify domain + app UUID. Add an HTTP Bearer credential containing your Coolify API token. Adjust the schedule interval (e.g., every 6 hours). Requirements Self-hosted n8n instance with /rest/settings endpoint accessible. Coolify (or a similar service) managing your n8n deployment. Valid API token configured as Bearer credential in n8n. How to customize Change the schedule frequency depending on how often you want checks. Modify the IF condition if you want stricter or looser version matching (e.g., ignore patch versions). Replace Coolify API call with another service (like Docker, Portainer, or Kubernetes) if you use a different deployment method. An n8n automation workflow template by Edoardo Guzzi.

By Julian Reich

This n8n template demonstrates how to automatically analyze all your accumulated notes from the past week and generate actionable insights, task lists, and priorities using AI. Use cases are many: Try automating weekly planning sessions, extracting action items from meeting notes, identifying recurring themes in your thoughts, or creating data-driven weekly reports for personal productivity tracking! Good to know ChatGPT analysis costs approximately $0.01-0.05 per week depending on the volume of notes The workflow uses advanced date filtering to process exactly 7 days of content Email sending requires SMTP configuration (Gmail, Outlook, etc.) Perfect companion:* Works seamlessly with the "Audio Notes to Google Docs*" workflow - it reads and analyzes all notes created by that system! How it works A schedule trigger runs every Sunday at your preferred time (default: 11 PM) The workflow reads your complete Google Doc containing all accumulated notes A smart filter function extracts only entries from the past 7 days using date stamp recognition The filtered content gets sent to ChatGPT which analyzes patterns and extracts: Actionable tasks for next week Important deadlines and appointments Key insights and learnings Top 3 priorities Category distribution (Work, Private, Health, etc.) A second AI call creates a personalized email summary with context and recommendations The structured analysis gets appended to your Google Doc as a weekly summary You receive a Telegram notification when the review is complete A detailed email report lands in your inbox with the full analysis and action items How to use The workflow runs automatically every Sunday - no manual intervention needed Adjust the schedule trigger to your preferred day/time for weekly planning Review the email summary and use the extracted tasks for your upcoming week planning The Google Doc serves as your permanent archive of weekly insights Requirements Google Docs API access to read your notes document OpenAI API account for ChatGPT analysis (GPT-4 recommended for best results) SMTP email configuration for sending summary reports Telegram Bot Token for notifications Prerequisite:* The *"Audio Notes to Google Docs**" workflow or similar system that creates timestamped entries Customising this workflow Modify the AI analysis prompt to focus on specific areas (business metrics, health tracking, learning goals) Add multiple analysis modes (daily, bi-weekly, monthly reviews) Include additional outputs like calendar event creation, task manager integration, or team sharing Connect to project management tools like Notion, Asana, or Monday.com for automatic task creation. An n8n automation workflow template by Julian Reich.

By Julian Reich

This n8n template demonstrates how to automatically convert voice messages from Telegram into structured, searchable notes in Google Docs using AI transcription and intelligent tagging. Use cases are many: Try capturing ideas on-the-go while walking, recording meeting insights hands-free, creating voice journals, or building a personal knowledge base from spoken thoughts! Good to know OpenAI Whisper transcription costs approximately $0.006 per minute of audio ChatGPT tagging adds roughly $0.001-0.003 per message depending on length The workflow supports both German and English voice recognition Text messages are also supported - they bypass transcription and go directly to AI tagging Perfect companion: Combine with the "Weekly AI Review**" workflow for automated weekly summaries of all your notes! How it works Telegram receives your voice message or text and triggers the workflow An IF node intelligently detects whether you sent audio or text content For voice messages: Telegram downloads the audio file and OpenAI Whisper transcribes it to text For text messages: Content is passed directly to the next step ChatGPT analyzes the content and generates up to 3 relevant keywords (Work, Ideas, Private, Health, etc.) A function node formats everything with Swiss timestamps, message type indicators, and clean structure The formatted entry gets automatically inserted into your Google Doc with date, keywords, and full content Telegram sends you a confirmation with the transcribed/original text so you can verify accuracy How to use Simply send a voice message or text to your Telegram bot - the workflow handles everything automatically The manual execution can be used for testing, but in production this runs on every message Voice messages work best with clear speech in quiet environments for optimal transcription Requirements Telegram Bot Token and configured webhook OpenAI API account for Whisper transcription and ChatGPT tagging Google Docs API access for document writing A dedicated Google Doc where all notes will be collected Customising this workflow Adjust the AI prompt to use different tagging categories relevant to your workflow (e.g., project names, priorities, emotions) Add multiple Google Docs for different contexts (work vs. private notes) Include additional processing like sentiment analysis or automatic task extraction Connect to other apps like Notion, Obsidian, or your preferred note-taking system And don't forget to also implement the complimentary workflow Weekly AI Review!. An n8n automation workflow template by Julian Reich.

By Davide Boizza

🎥🤖 This workflow automates the creation and publishing of UGC (User-Generated Content) videos using Google Gemini and Google Veo 3, then uploads them directly to Instagram with Postiz. Advantages ✅ Full Automation – Eliminates manual video editing, caption writing, and uploading. ✅ High-Quality UGC Videos – Leverages Google Veo 3 for professional ad-like video generation. ✅ AI-Powered Creativity – Uses Google Gemini for both creative direction and social media copywriting. ✅ Time-Saving – From image to published Instagram post in a single automated flow. ✅ Consistency – Ensures branding and messaging remain aligned across campaigns. ✅ Scalability – Can easily generate multiple UGC ads for different products. ✅ Centralized Management – Stores videos in Google Drive and distributes them via Postiz. How It Works Image Analysis & Creative Briefing: The workflow starts with a predefined product image. This image is analyzed by Google Gemini, which acts as a "Creative Director" to generate a detailed, cinematic prompt describing an 8-second commercial scene based on the image's content. Parallel AI Task Execution: The creative director's prompt is then sent to two different AI agents simultaneously: Video Generation: One agent uses the prompt with Google Veo 3 to generate the actual video file, visualizing the described scene. Copywriting: The other agent, acting as a "Social Media Manager," uses the same prompt to generate compelling caption copy tailored for an Instagram audience. Asset Distribution & Publishing: The generated video is uploaded to two destinations: Google Drive for storage and the Postiz API for social media management. The AI-generated caption is prepared. Finally, all data (video information from Postiz and the caption) is merged and sent to the Postiz node, which schedules and publishes the video as a post to the connected Instagram account. Set Up Steps To use this workflow, you need to configure the following credentials and node settings in n8n: Image Source: In the "Set image" node, replace the default image_url value with the URL of your own product image. Google Gemini Credentials: The workflow uses three Gemini nodes. Ensure your Google Gemini API credentials (named "Google Gemini(PaLM) (Eure)" in this example) are correctly set up and have access to the specified models (gemini-2.5-pro and veo-3.0-generate-preview). Google Drive Credentials: Configure the "Upload video" node with valid Google Drive OAuth credentials. Update the folderId parameter if you wish to save the generated videos to a different folder in your Drive. Postiz Credentials: The "Upload Video to Postiz" and "Instagram" nodes require valid credentials for the Postiz API. You must have an active Postiz account and have connected your Instagram business account to it within the Postiz platform. Postiz Integration ID: In the "Instagram" node, the integrationId field is specific to a connected social account within a Postiz account. You must replace this value with your own Instagram integration ID from Postiz. (Optional) Video Parameters: You can adjust the video generation aspect ratio (e.g., 9:16 for Stories/Reels) in the options of the "Generate UGC Video" node. Need help customizing? Contact me for consulting and support or add me on Linkedin. An n8n automation workflow template by Davide Boizza.

By WeblineIndia

Background Verification Executive Digest Automation: Track Completed & Pending Verifications via Email (from Google Sheets) This automation sends a daily late-night email summary to each Background Verification (BGV) executive — straight out of your “BGV Tracker” Google Sheet. Each executive gets their own digest listing candidates whose background checks were completed today and which ones are still pending, complete with clear “stale” alerts for overdue follow-ups. The workflow runs reliably via n8n, auto-grouping entries and packaging the results in a user-friendly tabular email, every day at 23:00 IST. Who’s it for BGV team leads & vendors** who want automatic updates on their queue. HR managers** looking to automate candidate tracking without manual report compilation. Ops teams** with Google Sheets-based BGV tracking wanting digest emails for each owner. Any organization managing candidate checks across multiple owners/executives. How it works Schedule Trigger: Runs every night at 23:00 IST (Asia/Kolkata), weekends OFF by default. Google Sheets: Reads all rows from your “BGV Tracker” (tab), using columns: candidate_name, previous_company, prevco_hr_name, prevco_hr_email bgv_status, last_follow_up, bgv_completion_date, bgv_executive, bgv_exe_email Code Node #1 (“Normalize & Parse”): Cleans and lower-cases all column names for consistency. Parses last_follow_up & bgv_completion_date from multiple local date formats. Adds helper flags: isCompletedToday, isStale (pending and last-follow-up ≥ 3 days). Code Node #2 (“Group & Filter”): Groups rows by bgv_exe_email (executive). Within each group: Segregates “Completed Today” and “Pending” items. Code Node #3 (“Format Digest”): Generates a personalized HTML email per executive, with two tables: Completed Today (with candidate/prevco info) Pending (with “stale” ⚠️ flags) Builds the subject line showing per-executive summary counts. Gmail Node: Sends the formatted email to each executive automatically. Can be customized for preview/test mode, CC or CSV attachments. How to set up Prepare Google Sheet: Create “BGV Tracker” tab (case-insensitive column names). Fill columns: candidate_name, previous_company, prevco_hr_name, prevco_hr_email, bgv_status, last_follow_up, bgv_completion_date, bgv_executive, bgv_exe_email n8n Configuration: Authenticate Google Sheets node (OAuth). Authenticate Gmail node (App Password recommended). Import workflow JSON and adjust credentials and sheet IDs. Test run (optional): Fill sample data in the sheet. Start workflow and review “dry run” outputs (optional). Activate workflow for daily auto-emails. Requirements A Google Sheet tab called “BGV Tracker” with supported columns. Gmail (SMTP or OAuth) credentials with permissions to send. n8n cloud or self-hosted, with Google and Gmail creds configured. How to customize Change run time:** Modify the Schedule Trigger for different hours/days. Weekend handling:** Add condition to skip Sat/Sun. Stale threshold:** Adjust the “>= 3 days” flag logic in code node. Email template:** Edit HTML layout, subject, header/footer as needed. Digest content:** Add/remove columns in the email tables within the code node. Preview/test mode:** Add a DRY_RUN variable and IF node for safe previewing before going live. Attachment/CC:** Add extra nodes to attach CSV, send summary to managers or post to Slack. Add‑ons Manager summary:** Aggregate all digests and send to HR head or ops manager. CSV exports:** Automatically attach filtered candidate lists per executive. Slack reminders:** DM executives with only their stale pending items. Auto-writeback:** Update next follow-up date in Sheet for stale cases. Use Case Examples BGV vendor:** Nightly queue email lets each checker focus on fresh items to close first. Recruiter audit:** HRBP gets an easy, nightly record of outstanding verifications, with overdue flags for fast escalation. Multi-client projects:** Divide the worksheet, send only relevant candidates to each exec, boosting clarity and compliance. Common Troubleshooting | Issue | Possible Cause | Solution | |-------------------------------|-------------------------------------------------|----------------------------------------------| | No emails sent | SMTP/Gmail credentials missing or expired | Re-authenticate Gmail node; check permissions| | Some candidates missing | Sheet has missing/invalid bgv_exe_email | Ensure every row has valid executive email | | Completed items not listed | Wrong/combo date formats in completion column | Use supported date format; ensure status="Completed" | | Pending doesn’t show stale | Last follow-up date out of expected format | Use supported date format & review data | | Workflow runs on weekends | Schedule misconfigured (or missed weekend filter)| Add/exclude Sat/Sun via config/node logic | | Pending pool includes “To be Sent” | Status filter in code not precise | Adjust code node filter to exclude explicitly| | Emails not delivered | Gmail sending limit exceeded | Add rate limit (wait node), check quota | Need Help? If you need a hand setting up, customizing or want to add more integrations (Slack, CSVs, approvals, etc.) reach out to us at WeblineIndia anytime. We can setup error handling, advanced templates and even help connect your flows to external systems!. An n8n automation workflow template by WeblineIndia.

By WeblineIndia

Sync Android drawable assets from Figma to GitHub via PR (multi‑density PNG) This n8n workflow automatically fetches design assets (icons, buttons) from Figma, exports them into Android drawable folder formats based on resolution (e.g., mdpi, hdpi, etc.) and commits them to a GitHub branch, creating a Pull Request with all updates. Who’s it for Android / Flutter developers** managing multiple screen densities. Design + Dev teams** wanting to automate asset delivery from Figma to codebase. Mobile teams** tired of manually exporting assets, resizing, organizing and uploading to GitHub. How it works Execute Flow manually or via trigger. Fetches all export URLs from a Figma file. Filters out only relevant components (Icon, Button). Prepares Android drawable folders for each density. Merges components with folder mapping. Calls Figma export API to get image URLs. Filters out empty/invalid URLs. Downloads all images as binary. Merges images with metadata. Renames and adjusts file names if needed. Prevents duplicate PRs using conditional checks. Commits files and opens a GitHub Pull Request. How to set up Set up your Figma token (with file access) Get Figma File Key and desired parent node ID Connect your GitHub account in n8n Prepare a GitHub branch for uploading assets Add your drawable folders config Adjust file naming logic as per your code style Run the workflow Requirements | Tool | Purpose | |------------------|-------------------------------------------| | Figma API Token | To fetch assets and export URLs | | GitHub Token | To commit files and open PR | | n8n | Workflow automation engine | | Figma File Key | Target design file | | Node Names | Named like Icon, Button | How to customize Add more component types** to extract (e.g., Avatar, Chip) Change drawable folder structure** for other platforms (iOS, Web) Add image optimization** before commit Switch from branch PR to direct commit** if preferred Add CI triggers** (e.g., Slack notifications or Jenkins trigger post-PR) Add‑ons Slack Notification Node Commit summary to CHANGELOG.md Image format conversion (e.g., SVG → PNG, PNG → WebP) Auto-tag new versions based on new asset count Use Case Examples Auto-export design changes as Android-ready assets Designers upload icons in Figma → Devs get PR with ready assets Maintain pixel-perfect assets per density without manual effort Integrate this into weekly design-dev sync workflows Common Troubleshooting | Issue | Possible Cause | Solution | |-----------------------------------|---------------------------------------------------|------------------------------------------------------------------------------| | Export URL is null | Figma node has no export settings | Add export settings in Figma for all components | | Images not appearing in PR | Merge or file name logic is incorrect | Recheck merge nodes, ensure file names include extensions | | Duplicate PR created | Condition node not properly checking branch | Update condition to check existing PR or use unique branch name | | Figma API returns 403/401 | Invalid or expired Figma token | Regenerate token and update n8n credentials | | GitHub file upload fails | Wrong path or binary input mismatch | Ensure correct folder structure (drawable-mdpi, etc.) and valid binary | | Assets missing certain resolutions| Not all resolutions exported in Figma | Export all densities in Figma, or fallback to default | Need Help? If you’d like help setting up, customizing or expanding this flow, feel free to reach out to our n8n automation team at WeblineIndia! We can help you: Fine-tune Figma queries Improve file renaming rules Integrate Slack / CI pipelines Add support for other platforms (iOS/Web) Happy automating!. An n8n automation workflow template by WeblineIndia.

By WeblineIndia

📊 Generate Weekly Energy Consumption Reports with API, Email and Google Drive This workflow automates the process of retrieving energy consumption data, formatting it into a CSV report, and distributing it every week via email and Google Drive. ⚡ Quick Implementation Steps: Import the workflow into your n8n instance. Configure your API, email details and Google Drive folder. (Optional) Adjust the CRON schedule if you need a different time or frequency. Activate workflow—automated weekly reports begin immediately. 🎯 Who’s It For Energy providers, sustainability departments, facility managers, renewable energy operators. 🛠 Requirements n8n instance Energy Consumption API access Google Drive account Email SMTP access ⚙️ How It Works Workflow triggers every Monday at 8 AM, fetches consumption data, emails CSV report and saves a copy to Google Drive. 🔄 Workflow Steps 1. Schedule Weekly (Mon 8:00 AM) Type: Cron Node Runs every Monday at 8:00 AM. Triggers the workflow execution automatically. 2. Fetch Energy Data Type: HTTP Request Node Makes a GET request to: https://api.energidataservice.dk/dataset/ConsumptionDE35Hour (sample API) The API returns JSON data with hourly electricity consumption in Denmark. Sample Response Structure: { "records": [ { "HourDK": "2025-08-25T01:00:00", "MunicipalityNo": _, "MunicipalityName": "Copenhagen", "ConsumptionkWh": 12345.67 } ] } 3. Normalize Records Type: Code Node Extracts the records array from the API response and maps each entry into separate JSON items for easier handling downstream. Code used: const itemlist = $input.first().json.records; return itemlist.map(r => ({ json: r })); 4. Convert to File Type: Convert to File Node Converts the array of JSON records into a CSV file. The CSV is stored in a binary field called data. 5. Send Email Weekly Report Type: Email Send Node Sends the generated CSV file as an attachment. Parameters: fromEmail: Sender email address (configure in node). toEmail: Recipient email address. subject: "Weekly Energy Consumption Report". attachments: =data (binary data from the previous node). 6. Report File Upload to Google Drive Type: Google Drive Node Uploads the CSV file to your Google Drive root folder. Filename pattern: energy_report_{{ $now.format('yyyy_MM_dd_HH_ii_ss') }} Requires valid Google Drive OAuth2 credentials. ✨ How To Customize Change report frequency, email template, data format (CSV/Excel) or add-ons. ➕ Add-ons Integration with analytics tools (Power BI, Tableau) Additional reporting formats (Excel, PDF) Slack notifications 🚦 Use Case Examples Automated weekly/monthly reporting for compliance Historical consumption tracking Operational analytics and forecasting 🔍 Troubleshooting Guide | Issue | Cause | Solution | |-------|-------|----------| | Data not fetched | API endpoint incorrect | Verify URL | | Email delivery issues | SMTP configuration incorrect | Verify SMTP | | Drive save fails | Permissions/Drive ID incorrect | Check Drive permissions | 📞 Need Assistance? Contact WeblineIndia for additional customization and support, we're happy to help. An n8n automation workflow template by WeblineIndia.

By Mahmoud Shrouf

Overview Automate your personal productivity with this intelligent n8n workflow that integrates Telegram, Google Sheets, and OpenAI (GPT-4o). This system uses multiple AI agents to manage work hours, tasks, finances, and emails—all through natural language commands sent via Telegram. Every action is synced to Google Sheets for persistent, structured data storage. What This Template Does This automation system deploys several specialized AI agents: 📊 Work Hours Analyzer**: Analyzes work logs from Google Sheets, calculates total hours by workplace, and generates detailed monthly reports in Arabic. 🛠️ Work Tracking Agent**: Handles start/end work commands, calculates total hours, and updates Google Sheets. 📋 Task Manager Agent**: Manages to-do lists—adding, listing, updating, completing, and deleting tasks—with real-time sync to Google Sheets. 💰 Finance Agent**: Tracks income and expenses in multiple currencies, summarizes daily financial activity, and maintains a full transaction history. 📧 Email Analysis Agent**: Processes incoming Gmail messages, generates AI-powered summaries in Arabic with priority, sentiment, and recommended actions. 📅 Monthly Report Generator**: Automatically triggers at the start of each month to compile a professional PDF report of work hours and sends it to a Telegram topic. Prerequisites & Setup Required Accounts & API Keys Before setup, ensure you have: Telegram Bot Token – from @BotFather OpenAI API Key – with access to gpt-4o-mini or gpt-3.5-turbo Google Sheets API – OAuth2 credentials enabled Gmail Account (Optional) – for email analysis n8n Instance – self-hosted or cloud Google Sheets Structure Create a Google Sheet with the following sheets and columns: Sheet: work Date start at end at place note Total hours Sheet: task Task Status Created At Due Date Notes Sheet: Expenses id Amount Currency Note Type (debit/credit) Date Time Sheet: email name email Step-by-Step Setup Step 1: Import the Workflow In n8n, go to Workflows > Import from file Upload the JSON template Open the canvas and verify all nodes are connected Step 2: Configure Credentials Telegram: Add your bot token under "Telegram account" OpenAI: Enter your API key in "OpenAi account" Google Sheets: Connect using OAuth2 under "Google Sheets account" Gmail (Optional): Set up if using email analysis Step 3: Link Google Sheets Share your Google Sheet with the service account email (if using service account) Copy the Document ID from the sheet URL Update all Google Sheets nodes with the correct sheet names and IDs Ensure column names match exactly Step 4: Set Up Telegram Start a chat with your bot Use /start to initialize Ensure chatId and message_thread_id in Telegram nodes match your group/topic Test sending a message like "Start work at the factory" Step 5: Test the Agents Try these sample commands via Telegram: "Start work at the factory" → Logs start time "Finished work" → Logs end time and calculates hours "Add task: pay the bill" → Adds a new task "How much did I spend today?" → Shows today’s expenses "Send last month's report" → Triggers monthly PDF report (on the first of the month) Key Features Smart Work Tracking Automatic time calculation Query by date, place, or period Real-time Google Sheets sync Task Management Add, list, update, complete, delete tasks Friendly, conversational responses Daily summaries of completed and upcoming tasks Financial Tracking Supports multiple currencies (JOD, USD, ILS, etc.) Daily income/expense summaries Full transaction history Arabic-language responses Email Intelligence AI-powered email summaries Priority, sentiment, and action recommendations Plain-text output in Arabic No JSON or code blocks Automated Monthly Reports Triggered on the 1st of each month Generates detailed work hour reports by workplace Outputs clean, formatted PDF Sends directly to Telegram topic Customization Options Modify AI Prompts Edit the systemMessage in any AI agent node to: Change tone (formal, friendly, concise) Add new response formats Support additional commands or languages Extend Functionality Add daily reminders using Schedule Trigger Implement budget alerts when expenses exceed a threshold Add weekly summaries for tasks or work hours Support multi-currency conversion Enhance Telegram Interaction Add inline buttons for quick actions Create shortcuts like /work, /tasks, /finance Use message_thread_id to organize topics Troubleshooting | Issue | Solution | |------|----------| | Bot not responding | Check webhook URL, bot token, and chatId | | Google Sheets not updating | Verify OAuth2 permissions and sheet sharing | | AI not understanding commands | Review prompt clarity and test input phrasing | | Monthly report not sending | Confirm Schedule Trigger timezone and execution time | Benefits ✅ Full automation with minimal user input 📱 Control everything from Telegram 📊 Data stored securely in Google Sheets 📄 Professional PDF reports generated automatically 💬 Natural, friendly Arabic responses 🔁 Seamless sync across all components This template transforms personal productivity by combining AI intelligence with powerful automation—turning simple Telegram messages into structured data, actionable insights, and professional reports. An n8n automation workflow template by Mahmoud Shrouf.

By WeblineIndia

Monthly Energy Generation Report (PostgreSQL → PDF → Email) This workflow automatically collects monthly energy generation data from a PostgreSQL database, converts it into a structured PDF report and emails it to stakeholders. It eliminates manual report creation and ensures timely delivery of performance summaries. Who’s it for Energy companies monitoring solar, wind or hydro generation Operations & maintenance (O\&M) teams needing monthly summaries Managers and executives who require periodic performance reports Data analysts who want automated reporting instead of manual exports How it works Monthly Trigger → Schedules the workflow to run once a month. Postgres Node → Fetches energy data from the energy_data table. Code Node (Transform Data) → Structures the raw records into JSON with metadata (date_range, records, note). HTTP Request (PDF.co API) → Converts structured data into a formatted PDF report. Gmail Node (Send Report) → Sends the PDF report (or link) via email to the configured recipient. How to set up Import the workflow JSON into n8n. Configure credentials: PostgreSQL connection (DB host, user, password, database, schema). Gmail OAuth2 credentials. PDF.co API key (for HTML → PDF conversion). Update: Database table (energy_data). Email recipients in the Gmail node. PDF template (if custom formatting is required). Activate workflow. Requirements n8n (self-hosted or cloud) PostgreSQL database with energy generation data PDF.co API account with valid API key Gmail account with OAuth2 access Internet access for API calls How to customize Change the SQL query in the Postgres node to filter specific plants or date ranges. Update the Code node to add extra fields (e.g., average power, anomalies). Modify the PDF.co request body to use a custom HTML template for branding. Replace Gmail with Outlook, SMTP, or Slack for distribution. Add-ons Add Slack/Teams node to notify teams when reports are sent. Store PDFs in Google Drive or S3 for archival. Add a dashboard (e.g., Grafana or Superset) that references the same DB for real-time view. Integrate with Jira to auto-create tasks for underperformance alerts. Use Case Examples Solar company emailing monthly reports to plant owners. Wind farm operator generating regulatory compliance reports. O&M teams automating KPI summaries for executives. Consulting firms monitoring multiple clients’ energy production. Common Troubleshooting | Issue | Possible Cause | Solution | | ------------------------------ | -------------------------------------- | ------------------------------------------------------- | | Workflow does not trigger | Cron not set correctly | Verify Schedule Trigger node interval is monthly | | No data returned from Postgres | Wrong schema/table or DB creds | Check DB connection and table name | | PDF not generated | Invalid/missing PDF.co API key | Generate a new key in PDF.co dashboard | | Email not sent | Gmail OAuth expired or wrong recipient | Reconnect Gmail credentials and confirm recipient email | | PDF output malformed | Incorrect JSON → HTML conversion | Check Code node formatting and PDF.co request body | Need Help? Our n8n workflow automation experts at WeblineIndia can help you: Set up the PostgreSQL connection securely, Customize the PDF layout with your company branding, Add more delivery channels (Slack, Teams, S3), Extend reporting logic (KPIs, charts, anomaly detection), And so much more. An n8n automation workflow template by WeblineIndia.

By Avkash Kakdiya

How it works This workflow starts when a user triggers a custom slash command in Slack. The workflow checks if a valid message (email address or HubSpot contact ID) was provided. Based on the input, it searches HubSpot for the contact either by email or by ID. Once the contact is found, the workflow formats the details into a clean, Slack-friendly message card and posts it back into the Slack channel. Step-by-step Start with Slack Slash Command The workflow is triggered whenever someone uses a custom slash command in Slack. It checks if the user actually entered something (email or ID). If nothing is entered, the workflow stops with an error. Parse Search Input The workflow cleans up the user’s input and determines whether it’s an email address or a HubSpot contact ID. This ensures the correct HubSpot search method is used. Search in HubSpot If the input is an email → the workflow searches HubSpot by email. If the input is an ID → the workflow retrieves the contact directly using the HubSpot contact ID. Format Contact Info The retrieved HubSpot contact details (name, email, phone, company, deal stage, etc.) are formatted into a Slack-friendly message card. Send Contact Info to Slack Finally, the formatted contact information is posted back into the Slack channel, making it instantly visible to the user and team. Why use this? Quickly look up HubSpot contacts directly from Slack without switching tools. Works with both email addresses and HubSpot IDs. Provides a clean, structured contact card in Slack with key details. Saves time for sales and support teams by keeping workflows inside Slack. Runs automatically once set up — no extra clicks or manual searches. An n8n automation workflow template by Avkash Kakdiya.

By Nijan

This workflow turns Slack into your content control hub and automates the full blog creation pipeline — from sourcing trending headlines, validating topics, drafting posts, and preparing content for your CMS. With one command in Slack, you can source news from RSS feeds, refine them with Gemini AI, generate high-quality blog posts, and get publish-ready output — all inside a single n8n workflow. ⸻ ⚙️ How It Works 1.Trigger in Slack Type start in a Slack channel to fetch trending headlines. Headlines are pulled from your configured RSS feeds. 2.Topic Generation (Gemini AI) Gemini rewrites RSS headlines into unique, non-duplicate topics. Slack displays these topics in a numbered list (e.g., reply with 2 to pick topic 2). 3.Content Validation When you reply with a number, Gemini validates and slightly rewrites the topic to ensure originality. Slack confirms the selected topic back to you. 4.Content Creation Gemini generates a LinkedIn/blog-style draft: Strong hook introduction 3–5 bullet insights A closing takeaway and CTA Optionally suggests asset ideas (e.g., image, infographic). 5.CMS-Ready Output Final draft is structured for publishing (markdown or plain text). You can expand this workflow to automatically send the output to your CMS (WordPress, Ghost, Notion, etc.). ⸻ 🛠 Setup Instructions Connect your Slack Bot to n8n. Configure your RSS Read nodes with feeds relevant to your niche. Add your Gemini API credentials in the AI node. Run the workflow: Type start in Slack → see trending topics. Reply with a number (e.g., gen 3) → get a generated blog draft in the same Slack thread. ⸻ 🎛 Customization Options • Change RSS sources to match your industry. • Adjust Gemini prompts for tone (educational, casual, professional). • Add moderation filters (skip sensitive or irrelevant topics). • Connect the final output step to your CMS, Notion, or Google Docs for publishing. ⸻ ✅ Why Use This Workflow? • One-stop flow: Sourcing → Validation → Writing → Publishing. • Hands-free control: Everything happens from Slack. • Flexible: Easily switch feeds, tone, or target CMS. • Scalable: Extend to newsletters, social posts, or knowledge bases. An n8n automation workflow template by Nijan.

By Eduard

This n8n template provides enterprise-level version control for your workflows using GitHub integration. Stop losing hours to broken workflows and manual exports – get proper commit history, visual diffs, and one-click rollbacks. This is the first template for n8n that provides real version control with commit-level granularity. Perfect for power users and tech teams managing multiple complex workflows. Animation demonstrates early bird version and may differ from the latest one How it works Automated sync**: Workflows are automatically synced to GitHub on your preferred schedule Smart categorization**: Dashboard shows which workflows are synced, n8n-only, or GitHub-only Complete commit history**: View every change with timestamps, authors, and commit messages Flexible import**: Import workflows from GitHub as new workflows or replace existing ones Individual workflow control**: Sync specific workflows with custom commit messages How to use Import the workflow template into your n8n instance Generate your n8n API key from your instance settings Configure your GitHub credentials and repository settings Set up the webhook endpoint for the dashboard interface Access the dashboard via the generated webhook URL Configure automatic sync schedule or use manual sync options Requirements n8n instance (cloud or self-hosted) with API access GitHub account and repository Basic understanding of Git workflows Customizing this workflow DIY or available as part of consulting services Professional customization for specific deployment workflows and integrations Custom sync schedules and commit message formats can be configured during setup. An n8n automation workflow template by Eduard.

By LeeWei

⚙️ Proposal Generator Template (Automates proposal creation from JotForm submissions) 🧑‍💻 Author: [LeeWei] 🚀 Steps to Connect: JotForm Setup Visit JotForm to generate your API key and connect to the JotForm Trigger node. Update the form field in the JotForm Trigger node with your form ID (default: 251206359432049). Google Drive Setup Go to Google Drive and set up OAuth2 credentials ("Google Drive account") with access to the folder containing your template. Update the fileId field in the Google Drive node with your template file ID (default: 1DSHUhq_DoM80cM7LZ5iZs6UGoFb3ZHsLpU3mZDuQwuQ). Update the name field in the Google Drive node with your desired output file name pattern (default: ={{ $json['Company Name'] }} | Ai Proposal). OpenAI Setup Visit OpenAI and generate your API key. Paste this key into the OpenAI and OpenAI1 nodes under the "OpenAi account 3" credentials. Update the modelId field in the OpenAI1 node if needed (default: gpt-4.1-mini). Google Docs Setup Set up OAuth2 credentials ("Google Docs account") with edit permissions for the generated documents. No fields need editing as the node dynamically updates based on previous outputs. Google Drive2 Setup Ensure the same Google Drive credentials ("Google Drive account") are used. No fields need editing as the node handles PDF conversion automatically. Gmail Setup Go to Gmail and set up OAuth2 credentials ("Gmail account"). No fields need editing as the node dynamically uses the prospect's email from JotForm. How it works The workflow triggers on JotForm submissions, copies a Google Drive template, downloads an audio call link, transcribes it with OpenAI, generates a tailored proposal, updates a Google Docs file, converts it to PDF, and emails it to the prospect. Set up steps Setup time: Approximately 15-20 minutes. Detailed instructions are available in sticky notes within the workflow. An n8n automation workflow template by LeeWei.

By Billy Christi

Who is this for? This workflow is perfect for: Support teams and customer service departments managing Jira tickets Team leads and managers who need daily visibility into ticket resolution progress Organizations wanting to automate ticket reporting and communication IT departments seeking to streamline support ticket summarization and tracking What problem is this workflow solving? Manual ticket review and reporting is time-consuming and often lacks comprehensive analysis. This workflow solves those issues by: Automating daily ticket analysis** by fetching, analyzing, and summarizing all tickets created each day Providing intelligent summaries** using AI to extract key insights from ticket descriptions, comments, and resolutions Streamlining communication** by automatically sending formatted daily reports to stakeholders Saving time** by eliminating manual ticket review and report generation What this workflow does This workflow automatically fetches daily Jira tickets, analyzes them with AI, and sends comprehensive summaries via email to keep your team informed about support activities. Step by step: Schedule Trigger runs the workflow automatically at your chosen interval (or manual trigger for testing) Set Project Key defines the Jira project to monitor (default: SUP project) Get All Tickets from the specified project created today Split Out extracts individual ticket data including key, summary, and description Loop Tickets processes each ticket individually through batch processing Get Comments from Ticket retrieves all comments and conversations for complete context Merge combines ticket data with associated comments for comprehensive analysis Ticket Summarizer (AI Agent) uses OpenAI GPT-5 to generate professional summaries and proposed solutions Set Output structures the AI analysis into standardized JSON format Aggregate collects all processed ticket summaries into a single dataset Format Body creates a readable email format with direct Jira ticket links Send Ticket Summaries delivers the daily report via Gmail How to set up Connect your Jira account by adding your Jira Software Cloud API credentials to the Jira nodes Add your OpenAI API key to the OpenAI Chat Model node for AI-powered ticket analysis Configure Gmail credentials for the Send Ticket Summaries node to deliver reports Update the recipient email in the "Send Ticket Summaries" node to your desired recipient Adjust the project key in the "Set Project Key" node to match your Jira project identifier Configure the schedule trigger to run daily at your preferred time for automatic reporting Customize the JQL query in Jira nodes to filter tickets based on your specific requirements Test the workflow using the manual trigger to ensure proper ticket fetching and AI analysis Review email formatting in the "Format Body" node and adjust as needed for your reporting style How to customize this workflow to your needs Modify AI prompts**: customize the ticket analysis prompt in the "Ticket Summarizer" node to focus on specific aspects like priority, resolution time, or customer impact Adjust ticket filters**: change the JQL queries to filter by status, priority, assignee, or custom date ranges beyond "today" Add more data points**: include additional ticket fields like priority, status, assignee, or custom fields in the analysis Customize email format**: modify the "Format Body" node to change the report structure, add charts, or include additional formatting Set up different schedules**: create multiple versions for different reporting frequencies (hourly, weekly, monthly) Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com. An n8n automation workflow template by Billy Christi.

By Billy Christi

Who is this for? This workflow is perfect for: Project managers and Agile teams who want to automate project setup and task creation Software development teams looking to standardize their project initialization process Business analysts and product owners who need to quickly convert project ideas into structured task breakdowns Companies using ClickUp for project management who want to leverage AI for intelligent project planning What problem is this workflow solving? Creating comprehensive project structures with detailed tasks and subtasks is time-consuming and often inconsistent. This workflow solves those issues by: Automating project creation** from initial concept to fully structured ClickUp project with tasks and subtasks Standardizing task breakdown** using AI to generate professional Agile user stories with proper descriptions Eliminating manual setup** while ensuring consistency across all projects and teams Improving project planning quality** through AI-driven task analysis and structured output What this workflow does This workflow transforms raw project ideas into complete, professional ClickUp projects with AI-generated task breakdowns and subtasks, following Agile best practices. Step by step: Form Trigger captures project details through a web form (Project Name and Full Features description) Project Naming AI Agent uses OpenAI to clean up project names, create professional descriptions, and generate random Jira-style project keys ClickUp Create List establishes the main project list in your ClickUp workspace Task Generator AI Agent analyzes project features and creates detailed task breakdown following Agile user story format Split Out breaks down the AI-generated task array into individual items for processing Loop Over Items processes each main task individually through batch processing ClickUp Create Task creates each main task with descriptions in the project list Split Out Subtasks extracts subtasks from each main task for individual processing Execute Sub-workflow triggers the subtask creation workflow to build parent-child task relationships Gmail Notification sends success notification email with project link and list ID Sub-workflow Loop handles individual subtask creation in ClickUp with proper parent task relationships How to set up Connect your OpenAI account by adding your API key to the OpenAI Chat Model node for AI-powered project analysis Configure ClickUp credentials by adding your ClickUp API key and updating team ID and space ID for your workspace Set up Gmail OAuth2 credential for sending notification emails Update email recipient in the Gmail node from the placeholder email to your actual email address Configure the Execute Workflow node to reference the correct sub-workflow ID for subtask creation Customize the form fields in the Form Trigger node based on your project input requirements Test the workflow with a sample project to ensure proper task generation and ClickUp integration Verify notifications are being sent correctly with proper project links How to customize this workflow to your needs Modify task generation prompts**: adjust the AI prompts in the Task Generator node to match your specific project methodology or industry requirements Add custom fields**: enhance the form trigger with additional project metadata fields like priority, team assignment, or project type Switch AI models**: replace the OpenAI Chat Model node with other AI providers like Google Gemini, Claude, or local models by using the appropriate n8n AI nodes for different cost and performance requirements Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com. An n8n automation workflow template by Billy Christi.

By Billy Christi

Who is this for? This workflow is perfect for: Agile development teams and project managers who need to quickly set up Jira projects Product managers who want to convert feature ideas into structured user stories and tasks Software development agencies that need to rapidly create detailed project structures for clients Scrum masters seeking to automate the initial project setup and backlog creation process What problem is this workflow solving? Creating comprehensive Jira projects with detailed user stories and sub-tasks is time-consuming and often inconsistent. This workflow solves those issues by: Automating project creation** from basic feature descriptions to fully structured Jira projects Generating professional user stories** following Agile best practices with proper "As a [user], I want to [goal], so that [benefit]" formatting Creating detailed sub-tasks** covering design, development, testing, and documentation phases What this workflow does This workflow transforms raw project ideas into fully structured Jira projects with comprehensive user stories and sub-tasks using AI-powered analysis and automated Jira integration. Step by step: Form Trigger collects project name and feature descriptions through a web form Project Naming uses GPT-4.1 mini to clean and professionalize the project name while generating a unique project key Create Project establishes a new Jira project with proper software development template and configuration Get Status ID retrieves project details and available issue types for story creation Jira Story Generator analyzes project features using AI to create structured user stories with sub-tasks Create Story generates individual Jira stories with proper titles and descriptions Execute Sub-task Workflow automatically creates all associated sub-tasks for each story Gmail Notification sends completion confirmation with project details and direct links How to set up Connect your Jira account by adding your Jira Software Cloud API credentials to all Jira-related nodes Update Jira URL in the "Set Jira URL" node to match your Jira instance (e.g., https://yourcompany.atlassian.net) Add OpenAI API key to the OpenAI Chat Model node for AI-powered story generation Configure Gmail credentials for the notification node and update the recipient email address Update project lead in the Create Project node by replacing the leadAccountId with your user ID Test the workflow using the manual trigger with sample project data Customize story templates in the Structured Output Parser if you need different story formats Set up the sub-workflow by ensuring the Execute Workflow node points to the correct workflow ID How to customize this workflow to your needs Adjust story generation prompts**: modify the AI prompts in the "Jira Story Generator" to match your team's specific story writing style or include additional fields Include estimation**: add story point estimation logic or time tracking fields to generated stories Switch AI models**: replace the OpenAI Chat Model node with other AI providers like Google Gemini, Claude, or local models by using the appropriate n8n AI nodes for different cost and performance requirements Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com. An n8n automation workflow template by Billy Christi.

By SuS

A guide to understand, operate, and extend the workflow. 1) What this workflow does (and why it’s useful) Goal: Turn a simple Airtable sheet into a content calendar that automatically publishes Instagram Reels via the Instagram Graph API, on a schedule you control in n8n. Why this matters: Your team plans everything in Airtable (user-friendly, collaborative). n8n** posts for you at the right time, every time. You keep full control (no third-party SaaS lock-in, no manual uploads). Later, you can reuse the same queue to post YouTube Shorts / TikTok (omnichannel). Core flow (one row = one post): Cron starts the workflow at a set time. Airtable – Search grabs due rows: status = "To Post" AND scheduled_at <= NOW() AND platform = "IG". Split Out processes each row individually. Set (Map fields) normalizes Airtable fields → video_url, caption, recordId. IG: Create Media Container registers your video as REEL. Wait 90s lets IG process the video. IG: Publish Reel publishes the container. Airtable – Update marks the row as Posted, stores ig_media_id, and timestamp. 2) Architecture at a glance [Cron] → [Airtable: Search records] → [Split Out: records] → [Set: Map fields] → [IG: Create Media Container] → [Wait 90s] → [IG: Publish Reel] → [Airtable: Update record] Sticky Notes inside the workflow explain each step (they’re rendered from parameters.content with Markdown). 3) Airtable schema (recommended) Create a table (e.g., Posts) with these fields: | Field | Type | Purpose | |---------------|-----------------|-------------------------------------------------------| | video_url | URL or Text | Directly accessible (public) URL to your MP4 | | caption | Long text | Final caption (hashtags, line breaks, emojis) | | platform | Single select | Set IG for this workflow | | status | Single select | To Post → will be picked up; Posted later | | scheduled_at| Date/Time (UTC) | When to post | | ig_media_id | Text (optional) | Filled by n8n after publishing | | posted_at | Date/Time | Filled by n8n after publishing | Filter used in the Airtable “Search records” node: AND({status}='To Post', {scheduled_at}<=NOW(), {platform}='IG') > Tip: If you localize/rename fields, update the filter accordingly. 4) Prerequisites & credentials Instagram Business/Creator* account connected to a *Facebook Page**. IG User ID** for the connected account. Long-lived IG Access Token** with permissions to create and publish content. n8n environment variables** (Settings → Environments): IG_API_VERSION (e.g., v21.0) IG_USER_ID IG_ACCESS_TOKEN Airtable credential* in n8n using a *Personal Access Token** (as in your example). A publicly accessible video_url (e.g., S3/GCS signed URL, public CDN, Drive/Dropbox direct link). The API pulls from your URL; it cannot fetch files behind logins. 5) Node-by-node deep dive (what each node expects/returns) A) Cron Trigger What it does:** Starts the workflow on a schedule (daily at 09:00 in the template). How to use:** Adjust hours/minutes to your cadence (hourly, twice a day, etc.). B) Airtable: Search records Operation:** search Base/Table:** Select from dropdowns (matches your account). Options → filterByFormula:** AND({status}='To Post', {scheduled_at}<=NOW(), {platform}='IG') Return:** An array under records[]. Each record has id and fields. C) Split Out: records What it does:** Turns the records[] array into individual items. Why:** Downstream steps can then act on each post separately. D) Set: Map fields What it does:** Normalizes data to predictable keys and keeps the recordId. Outputs:** recordId = {{$json.id}} video_url = {{$json.fields.video_url}} caption = {{$json.fields.caption}} scheduled_at = {{$json.fields.scheduled_at}} E) IG: Create Media Container (REELS) Endpoint:** POST https://graph.facebook.com/{v}/{ig-user-id}/media Body params:** video_url = {{$json.video_url}} caption = {{$json.caption}} media_type=REELS share_to_feed=true (optional) access_token=${IG_ACCESS_TOKEN} Return:* JSON with *container id** under id (this is your creation_id for publishing). F) Wait 90s Why:** IG needs time to process the video behind video_url. Tip:** If your videos are large or high bitrate, you may increase to 120–180s. G) IG: Publish Reel Endpoint:** POST https://graph.facebook.com/{v}/{ig-user-id}/media_publish Body params:** creation_id = {{$json.id}} (the container id from step E) access_token = ${IG_ACCESS_TOKEN} Return:* JSON with *id = ig_media_id** (the published media). H) Airtable: Update record What it does:** Writes results back to the same row. Fields updated (example):** status = "Posted" ig_media_id = {{$json.id}} posted_at = {{$now}} 6) First-run checklist (do this once) In both Airtable nodes, pick your Base and Table (via dropdown). Confirm filterByFormula matches your field names exactly. Add one test row in Airtable: video_url = a public MP4 URL caption = a small caption platform = IG status = To Post scheduled_at = in the past (so it’s due now) Set Cron to run in the next minute (or click Execute Workflow manually). Confirm the flow: Airtable search → returns 1 record Container created → you get an id After 90s → Publish returns a media id Airtable updated → row becomes Posted with ig_media_id and posted_at 7) Daily operations (how to use it day-to-day) Your team fills Airtable with upcoming posts. Keep status = To Post, set accurate scheduled_at in UTC. n8n’s Cron checks regularly and posts due items. After publishing, the row is marked Posted (so it won’t re-post). Backfilling: If you need to post a bunch of older content, set scheduled_at in the past for those rows and let Cron pick them up. If needed, run the workflow manually. An n8n automation workflow template by SuS.

By Calistus Christian

Summary Turns the latest CVEs from NVD into a clean, sortable email digest (table + plaintext) and sends it via Gmail. The flow pulls the newest CVEs, extracts Vendor / Product / Version, severity & CVSS, highlights public exploit references, drafts an HTML table, then asks OpenAI to tighten the copy before emailing it. Optionally, you can swap the Gmail node to Signal, Slack, Microsoft Teams, etc. Perfect for: SecOps leads who want a low-noise digest of what changed recently, grouped and ranked by severity. * What this workflow does Triggers on a schedule (every 30 minutes by default). Calls the NVD 2.0 API to fetch recent CVEs. Parses each CVE to extract: Vendor / Product / Version(s) (from CPE 2.3 where available, with a text fallback) Severity + CVSS (V3.1/V3.0/V2 fallback) and vector string Exploit signal (tags/links like Exploit‑DB, GitHub PoCs, etc.) Short English summary + direct NVD link Builds an HTML email (and a plaintext fallback) ranked by severity then score. Uses OpenAI to polish the subject line and copy into a concise, professional digest (JSON‑only contract). Sends the digest with the Gmail node. * Prerequisites NVD API key** (free) --- create at https://nvd.nist.gov/developers/request-an-api-key OpenAI API key** with access to gpt-4o-mini (or change the model) Email sending**: Gmail node with OAuth2 (recommended), or swap to the generic Email Send (SMTP) node if you prefer. Quick start Import the workflow JSON below. Open HTTP Request → Headers and confirm apiKey uses {{$env.NVD_API_KEY}}. Open Send a message (Gmail) and set To to {{$env.RECIPIENT_EMAIL}} (or your address). Open OpenAI Email Crafter and connect your OpenAI credential (or change model if needed). Hit Execute to test, then Activate when happy. Credits Created by ca7ai (n8n Creator). * Tags security, cve, cisa, nvd, email, monitoring, openai, gmail, automation. An n8n automation workflow template by Calistus Christian.

By Luís Philipe Trindade

What’s up guys, I’m Luís 🙋🏻‍♂️ If you manage learning programs, communities, or customer groups on WhatsApp, this workflow will save your life. It’s your AI-powered FAQ engine. This workflow captures group conversations (via Google Sheets), identifies the most common doubts and recurring questions, and automatically builds a structured FAQ document with suggested answers. ⚠️ Important note To use this workflow, you must already have all WhatsApp conversations saved into a Google Sheet. If you don’t have this yet, check out my other workflow that does exactly that: Workflow to Summary Group WhatsApp. ✅ What this workflow does Runs weekly (every Monday 6am) Pulls all conversations from your Google Sheet Groups messages by week into structured blocks Sends blocks to an AI Agent to detect FAQs AI extracts recurring questions, explains context, and suggests answers Creates a new FAQ document in Google Docs based on a template Keeps everything organized and accessible for the team 🧩 Flow Structure Part 1 – Data Capture & Weekly Blocks Retrieves group messages from Google Sheets Organizes them by ISO week number Prepares clean message blocks for AI analysis Part 2 – AI FAQ Builder AI Agent analyzes the messages Extracts FAQs with suggested responses Generates a new Google Doc FAQ every week 🔧 Tools used ✅ Google Sheets (message log database) ✅ OpenAI (AI analysis & FAQ generation) ✅ Google Docs (automatic FAQ output) ✅ Schedule Trigger (weekly automation) 🌟 Why this workflow stands out 📊 Turns raw WhatsApp conversations into weekly FAQ reports 🤖 AI not only detects questions, but also suggests answers 🚀 Automated, scalable and perfect for communities and teams 📝 Delivers a ready-to-use FAQ doc every week ✅ Works on both n8n Cloud and Self-hosted 🔐 100% secure. No hacks. No shortcuts. Want to adapt this flow for your business, education program, or internal team? 📩 Custom requests: WhatsApp me at +55 34 99256-9346 🇧🇷 Português (PT-BR) Fala, galera! Eu sou o Luís 🙋🏻‍♂️ Se você gerencia cursos, comunidades ou grupos de clientes no WhatsApp, esse fluxo vai salvar sua vida. É o seu FAQ automático com IA. Ele pega as conversas que já estão salvas em uma planilha do Google Sheets, identifica as dúvidas mais recorrentes e gera um documento organizado com respostas sugeridas. ⚠️ Atenção Para usar esse fluxo, você precisa já ter todas as conversas do WhatsApp salvas em uma planilha no Google Sheets. Se você ainda não tem isso configurado, utilize meu outro workflow que faz exatamente esse processo: Workflow to Summary Group WhatsApp. ✅ O que esse fluxo faz Roda toda segunda-feira às 6h Busca as mensagens salvas em sua planilha no Google Sheets Agrupa por semana em blocos organizados Envia para um Agente de IA que identifica dúvidas recorrentes Gera explicações e respostas sugeridas Cria automaticamente um novo documento FAQ no Google Docs Mantém um histórico semanal claro e acessível 🧩 Como o fluxo está estruturado Parte 1 – Captura & Blocos Semanais Puxa mensagens da planilha Organiza por semana ISO Prepara blocos para análise pela IA Parte 2 – FAQ Builder com IA Agente de IA analisa blocos Extrai dúvidas recorrentes e sugere respostas Cria um documento FAQ atualizado no Google Docs 🔧 Ferramentas utilizadas ✅ Google Sheets (base de mensagens) ✅ OpenAI (análise & geração de FAQ) ✅ Google Docs (documento automático) ✅ Agendamento semanal (gatilho) 🌟 Por que esse fluxo se destaca 📊 Transforma mensagens de grupo em relatórios semanais de FAQ 🤖 IA identifica dúvidas e já entrega respostas prontas 🚀 Escalável para qualquer comunidade ou programa educacional 📝 Documento novo toda semana, sem esforço manual ✅ Compatível com n8n Cloud e Self-hosted 🔐 100% seguro. Sem gambiarras. Quer adaptar esse fluxo pro seu negócio, curso ou comunidade? 📩 Solicitação personalizada: me chama no WhatsApp +55 34 99256-9346. An n8n automation workflow template by Luís Philipe Trindade.

By Sergey Skorobogatov

📈 AI Stock Analytics & BCS "Profit" Social Network Publishing Workflow This workflow automatically generates stock market insights for selected tickers (e.g. GAZP, SBER, LKOH) using historical data, technical indicators, and an AI model. The results are then sent to Telegram for quick moderation and publishing. 🔑 What this workflow does Runs twice a day** on a schedule with a predefined list of tickers. Fetches historical market data** from a broker API. Calculates key technical indicators** (RSI, EMA/SMA, MACD, Bollinger Bands, ADX). Generates an investment post** (title + summary) using an LLM. Stores results** in a PostgreSQL database. Sends a draft post to Telegram* with inline buttons *“Publish” and “Retry”. Handles Telegram actions**: publishes the post to the final channel or re-runs the generation process. 📌 Key features Multi-ticker support in a single run. Automatic error handling (e.g. missing data or invalid AI JSON output). Human-in-the-loop moderation through Telegram before publishing. PostgreSQL integration for history and analytics storage. Flexible structure: easy to extend with new tickers, indicators, or publishing channels. 🛠️ Nodes used Trigger:** Schedule (twice daily) + Telegram Trigger (button callbacks). Data:** HTTP Request (broker API), Function (technical analysis calculations). AI:** OpenAI / OpenRouter with structured JSON output. Storage:** PostgreSQL (analytics history). Messaging:** Telegram (drafts and publishing). 🚀 Who is this for Fintech startups looking to automate market content. Investment bloggers posting daily stock analysis. Analysts experimenting with trading strategies on real market data. An n8n automation workflow template by Sergey Skorobogatov.

By SuS

📊 YouTube Trends Workflow in n8n 🎯 Goal of the Workflow This workflow fetches the most popular YouTube videos in Germany and transforms them into a clean list of trending hashtags/keywords. It’s not just raw data – it highlights qualitative insights about which topics and keywords drive real engagement. Useful for: Content creators & marketers** → quick inspiration for viral topics SEO/hashtag research** → discover high-performing keywords Social media teams** → automated trend reporting ⚙️ How It Works – Step by Step 1. Trigger Node:** Manual Trigger Entry point of the workflow. → Can later be replaced with a Cron or Webhook trigger to run automatically. 2. API Call – YouTube Node:** HTTP Request Calls the YouTube Data API v3 with: chart=mostPopular regionCode=DE maxResults=50 Returns a list of trending videos in Germany, including title, channel, views, likes, comments, and tags. 3. Split Items Node:** Split Out Splits the API response (items[]) into individual items, so each video is processed separately. 4. Context & KPIs Node:** Set Extracts key fields: title, channel, publishedAt views, likes, comments Calculates: engagementRate = (likes + comments) / (views + 1) Why? Looking at views alone is misleading. Engagement rate reveals which videos truly resonate with the audience. 5. Ranking & Limit Node:** Item Lists Sorts videos by highest engagement rate (descending). Limits results to the Top 20 videos. Why? This reduces noise and focuses only on the most relevant trends. 6. Collect Tags Node:** Aggregate Collects all snippet.tags from the top videos. Merges them into a single keyword list. 7. Keyword Summary Node:** Summarize Concatenates all collected tags into one string. Result: A compact hashtag/keyword list → ready to use for: Content ideas SEO/hashtag strategies Social media planning 📈 Why This Workflow Is Useful Automated trend analysis**: no need to manually browse YouTube. Quality focus**: uses engagement rate, not just views. Reusable**: results can be: stored in Google Sheets or Airtable, sent to Slack/Telegram, or used in a dashboard. 🚀 Possible Extensions Cron Trigger** → run daily for automated reports. Notifier** → send results directly to Slack, Discord, or Telegram. Storage** → save trends in a database for historical analysis. AI Node** → use GPT to summarize trends into “3 key insights of the day.” ✅ Conclusion With a few smartly combined nodes, this workflow: fetches external API data (YouTube), cleans and enriches it, calculates qualitative KPIs, and delivers actionable trend insights. Perfect as a community showcase or a practical tool for creators and marketers. An n8n automation workflow template by SuS.

By Caio Garvil

Automate Colombian Cashflow Data Extraction to Google Sheets with AI Who’s it for This workflow is designed for finance professionals, accountants, small business owners in Colombia, or anyone needing to automate the extraction of invoice data and its entry into Google Sheets. It's particularly useful for handling Colombian tax and legal specifics. How it works / What it does This workflow automates the process of extracting critical data from invoices and receipts (PDFs and JPEGs) and organizing it in a Google Sheet: Triggers:** The workflow initiates when a new file is created or an existing file is updated in a designated Google Drive folder. File Handling:** It first downloads the detected file. Routing:** A "Switch" node intelligently routes the file based on its extension – one path for PDFs and another for JPEGs. Data Extraction:** For PDF files, it directly extracts all text content from the document. For JPEG image files, it utilizes an AI Agent (Azure OpenAI) to process the image and extract its textual content. AI-Powered Reasoning:** Two "Reasoning Agent" nodes (Azure OpenAI Chat Models) act as a specialized "Colombian Tax and Legal Extraction Agent". They parse the extracted text from invoices to pull out structured data in JSON format, including: Vendor name. Modification date. Line items with detailed description, sub_total, iva_value, total_amount, category, and sub_category. Specific Colombian tax fields like Retefuente and ReteICA. The number of items generated. Output Parsing:** A "Structured Output Parser" node ensures that the AI's output strictly adheres to a predefined JSON schema, guaranteeing consistent data formatting. Data Preparation:** "Edit Field" nodes ensure the AI's extracted data is in a valid format. Item Splitting:** "Split data" nodes separate the 'items' array from the AI's output, allowing each individual line item from the invoice to be processed as a separate entry for the Google Sheet. Google Sheet Integration:** Finally, "Fill Template" nodes append the fully processed invoice data (per line item) into your designated Google Sheet. How to set up Google Drive Credentials: Ensure you have configured your Google Drive OAuth2 API credentials in n8n. Azure OpenAI Credentials: Set up your Azure OpenAI API credentials, ensuring access to models like gpt-4o. Or you can simply use your traditional OpenAI or others LLMs. Google Sheets Credentials: Configure your Google Sheets OAuth2 API credentials. Google Drive Folder ID: In the "1a. Updated file trigger" and "1b. Created file trigger" nodes, update the folderToWatch parameter with your specific Google Drive Folder ID. Google Sheet ID and Sheet Name: In the "8. Fill Template" and "8. Fill Template1" nodes, update the documentId and sheetName parameters with your specific Google Sheet ID and the name of the sheet where data should be appended. Requirements An active n8n instance. A Google Drive account for file uploads. A Google Sheets account for data storage. An Azure OpenAI account with access to chat models (e.g., gpt-4o) for the "Azure OpenAI Chat Model" nodes and "Extract Data Agent". How to customize the workflow AI Extraction Prompts:** Modify the prompt instructions in the "5. Reasoning Agent" and "5. Reasoning Agent1" nodes if you need to extract different data points or change the output format. Google Sheet Column Mappings:** Adjust the columns mapping in the "8. Fill Template" and "8. Fill Template1" nodes to match your specific Google Sheet headers and data requirements. File Types:** Extend the "3. Route" node to handle additional file types (e.g., DOCX, PNG) by adding new conditions and corresponding extraction nodes. An n8n automation workflow template by Caio Garvil.

By Javier Quilez Cabello

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow automates the registration of event participants in SinergiaCRM from a Google Sheets spreadsheet. A Google Sheets Trigger watches for new rows with pending registrations. The flow checks if the participant already exists in SinergiaCRM by NIF (national ID). If the contact exists, it creates a relationship and registers them for an event. If the contact doesn’t exist, it first creates the contact, then adds the relationship and event registration. Finally, it marks the row as "Processed" in the original spreadsheet to avoid duplicate entries. Set up steps Connect your Google Sheets and SinergiaCRM accounts using OAuth credentials. Replace the sample Google Sheet ID and worksheet name with your own. Ensure the spreadsheet contains the following columns: First name, Last name, NIF, Email, Event ID, Relation type, Registration date, and Relation date. Add the appropriate values in the "To CRM" and "Processed" columns to control processing logic. Review sticky notes inside the workflow for additional guidance and customization tips. An n8n automation workflow template by Javier Quilez Cabello.

By Viktor Klepikovskyi

Simple REST API with Google Sheets Introduction This workflow template demonstrates how to quickly and easily create a simple REST API using n8n and a Google Sheet as a no-code database. It's a perfect starting point for building a backend for small applications, prototypes, or internal tools without writing any code. Purpose The purpose of this template is to provide a complete, ready-to-use n8n workflow that handles all fundamental CRUD (Create, Read, Update, Delete) operations. The workflow uses a single Webhook trigger to handle POST, GET, PUT, and DELETE requests, allowing you to manage data in your Google Sheet through standard API calls. Setup Instructions To get started with this template, follow these steps: Prepare your Google Sheet: Create a new Google Sheet and add the following column headers in the first row: name, email, and status. You can use this example Google Sheet as a starting point. This sheet will serve as your database. Authenticate: In the n8n workflow, connect your Google Account credentials to the Google Sheets nodes. Select your data: Choose the Google Sheet and the corresponding sheet name from the drop-down lists in each of the Google Sheets nodes. Activate: Save and activate the workflow. Test the API: Use a tool like curl, Postman, or Insomnia to test your new API endpoints. The base URL will be your n8n webhook URL followed by /items. Example curl Commands: POST (Create):** curl -X POST YOUR_N8N_WEBHOOK_URL/items -H "Content-Type: application/json" -d '{"name": "Alice", "email": "alice@example.com", "status": "active"}' GET (Read All):** curl -X GET YOUR_N8N_WEBHOOK_URL/items/all GET (Read Single):** curl -X GET YOUR_N8N_WEBHOOK_URL/items?id=2 PUT (Update):** curl -X PUT YOUR_N8N_WEBHOOK_URL/items?id=2 -H "Content-Type: application/json" -d '{"status": "inactive"}' DELETE (Delete):** curl -X DELETE YOUR_N8N_WEBHOOK_URL/items?id=2 For more detailed instructions, including building the workflow in n8n, check out the full blog post: Build a Simple REST API in 10 Minutes with n8n & Google Sheets. An n8n automation workflow template by Viktor Klepikovskyi.