Workflow Templates

The AI Blog Creator with Gemini, Replicate Image, Supabase Publishing & Slack is a fully automated content generation and publishing workflow designed for modern marketing and SaaS teams. It automatically fetches the latest industry trends, generates SEO-optimized blogs using AI, creates a relevant featured image, publishes the post to your CMS (e.g., Supabase or custom API), and notifies your team via Slack all on a daily schedule. This workflow connects multiple services NewsAPI, Google Gemini, Replicate, Supabase, and Slack into one intelligent content pipeline that runs hands-free once set up. ✨ Features 📰 Fetch Trending Topics — pulls the latest news or updates from your selected industry (via NewsAPI). 🤖 AI Topic Generation — Gemini suggests trending blog topics relevant to AI, SaaS, and Automation. 📝 AI Blog Authoring — Gemini then writes a full 1200-1500 word SEO-optimized article in Markdown. 🧹 Smart JSON Cleaner — A resilient code node parses Gemini’s output and ensures clean, structured data. 🖼️ Auto-Generated Image — Replicate’s Ideogram model creates a blog cover image based on the content prompt. 🌐 Automatic Publishing — Posts are automatically published to your Supabase or custom backend. 💬 Slack Notification — Notifies your team with blog details and live URL. ⏰ Fully Scheduled — Runs automatically every day at your preferred time (default 10 AM IST). ⚙️ Workflow Structure | Step | Node | Purpose | | ---- | ----------------------------------- | ----------------------------------------------- | | 1 | Schedule Trigger | Runs daily at 10 AM | | 2 | Fetch Industry Trends (NewsAPI) | Retrieves trending articles | | 3 | Message a model (Gemini) | Generates trending topic ideas | | 4 | Message a model1 (Gemini) | Writes full SEO blog content | | 5 | Code in JavaScript | Cleans, validates, and normalizes Gemini output | | 6 | HTTP Request (Replicate) | Generates an image using Ideogram | | 7 | HTTP Request1 | Retrieves generated image URL | | 8 | Wait + If | Polls until image generation succeeds | | 9 | Edit Fields | Assembles blog fields into final JSON | | 10 | Publish to Supabase | Posts to your CMS | | 11 | Slack Notification | Sends message to your Slack channel | 🔧 Setup Instructions Import the Workflow in n8n and enable it. Create the following credentials: NewsAPI (Query Auth) — from https://newsapi.org Google Gemini (PaLM API) — use your Gemini API key Replicate (Bearer Auth) — API key from https://replicate.com/account Supabase (Header Auth) — endpoint to your /functions/v1/blog-api (set your key in header) Slack API — create a Slack App token with chat:write permission Edit the NewsAPI URL query parameter to match your industry (e.g., q=AI automation SaaS). Update the Supabase publish URL to your project endpoint if needed. Adjust the Slack Channel name under “Slack Notification”. (Optional) Change the Schedule Trigger time as per your timezone. 💡 Notes & Tips The Code in JavaScript node is robust against malformed or extra text in Gemini output — it sanitizes Markdown and reconstructs clean JSON safely. You can replace Supabase with any CMS or Webhook endpoint by editing the “Publish to Supabase” node. The Replicate model used is ideogram-ai/ideogram-v3-turbo — you can swap it with Stable Diffusion or another model for different aesthetics. Use the slug field in your blog URLs for SEO-friendly links. Test with one manual execution before activating scheduled runs. If Slack notification fails, verify the token scopes and channel permissions. 🧩 Tags #AI #Automation #ContentMarketing #BlogGenerator #n8n #Supabase #Gemini #Replicate #Slack #WorkflowAutomation

⚠️ Note: This template requires a community node and works only on self-hosted n8n installations. It uses the Typhoon OCR Python package, pdfseparate from poppler-utils, and custom command execution. Make sure to install all required dependencies locally. Who is this for? This template is designed for developers, back-office teams, and automation builders (especially in Thailand or Thai-speaking environments) who need to process multi-file, multi-page Thai PDFs and automatically export structured results to Google Sheets. It is ideal for: Government and enterprise document processing Thai-language invoices, memos, and official letters AI-powered automation pipelines that require Thai OCR What problem does this solve? Typhoon OCR is one of the most accurate OCR tools for Thai text, but integrating it into an end-to-end workflow usually requires manual scripting and handling multi-page PDFs. This template solves that by: Splitting PDFs into individual pages Running Typhoon OCR on each page Aggregating text back into a single file Using AI to extract structured fields Automatically saving structured data into Google Sheets What this workflow does Trigger:** Manual execution or any n8n trigger node Load Files:** Read PDFs from a local doc/multipage folder Split PDF Pages:** Use pdfinfo and pdfseparate to break PDFs into pages Typhoon OCR:** Run OCR on each page via Execute Command Aggregate:** Combine per-page OCR text LLM Extraction:** Use AI (e.g., GPT-4, OpenRouter) to extract fields into JSON Parse JSON:** Convert structured JSON into a tabular format Google Sheets:** Append one row per file into a Google Sheet Cleanup:** Delete temp split pages and move processed PDFs into a Completed folder Setup Install Requirements Python 3.10+ typhoon-ocr: pip install typhoon-ocr poppler-utils: provides pdfinfo, pdfseparate qpdf: backup page counting Create folders /doc/multipage for incoming files /doc/tmp for split pages /doc/multipage/Completed for processed files Google Sheet Create a Google Sheet with column headers like: book_id | date | subject | to | attach | detail | signed_by | signed_by2 | contact_phone | contact_email | contact_fax | download_url API Keys Export your TYPHOON_OCR_API_KEY and OPENAI_API_KEY (or use credentials in n8n) How to customize this workflow Replace the LLM provider in the “Structure Text to JSON with LLM” node (supports OpenRouter, OpenAI, etc.) Adjust the JSON schema and parsing logic to match your documents Update Google Sheets mapping to fit your desired fields Add trigger nodes (Dropbox, Google Drive, Webhook) to automate file ingestion About Typhoon OCR Typhoon is a multilingual LLM and NLP toolkit optimized for Thai. It includes typhoon-ocr, a Python OCR package designed for Thai-centric documents. It is open-source, highly accurate, and works well in automation pipelines. Perfect for government paperwork, PDF reports, and multi-language documents in Southeast Asia. Deployment Option You can also deploy this workflow easily using the Docker image provided in my GitHub repository: https://github.com/Jaruphat/n8n-ffmpeg-typhoon-ollama This Docker setup already includes n8n, ffmpeg, Typhoon OCR, and Ollama combined together, so you can run the whole environment without installing each dependency manually.

Automatically creates complete videos from a text prompt—script, voiceover, stock footage, and subtitles all assembled and ready. How it works Send a video topic via webhook (e.g., "Create a 60-second video about morning exercise"). The workflow uses OpenAI to generate a structured script with scenes, converts text to natural-sounding speech, searches Pexels for matching B-roll footage, and downloads everything. Finally, it merges audio with video, generates SRT subtitles, and prepares all components for final assembly. The workflow handles parallel processing—while generating voiceover, it simultaneously searches and downloads stock footage to save time. Setup steps Add OpenAI credentials for script generation and text-to-speech Get a free Pexels API key from pexels.com/api for stock footage access Connect Google Drive for storing the final video output Install FFmpeg (optional) for automated video assembly, or manually combine the components Test the webhook by sending a POST request with your video topic Input format: { "prompt": "Your video topic here", "duration": 60, "style": "motivational" } What you get ✅ AI-generated script broken into scenes ✅ Professional voiceover audio (MP3) ✅ Downloaded stock footage clips (MP4) ✅ Timed subtitles file (SRT) ✅ All components ready for final editing Note: The final video assembly requires FFmpeg or a video editor. All components are prepared and organized by scene number for easy manual editing if needed.

Who’s it for? Content Creators E-commerce Stores Marketing Team Description: Generate unique UGC images for your products. Simply upload a product image into a Google Drive folder, and the workflow will instantly generate 50 unique, high-quality AI UGC images using Nano Banana via Fal.ai. All results are automatically saved back into the same folder, ready to use across social media, e-commerce stores, and marketing campaigns. How it works? 📺 YouTube Video Tutorial: 1 - Trigger: Upload a new Product Image (with white background) to a Folder in your Google Drive 2 - Generate 50 different Image Prompts for your Product 3 - Loop over each Prompt Generated 4 - Generate UGC Content thanks to Fal.ai (Nano Banana) 5 - Upload UGC Content on the initial Google Drive Folder Cost: 0.039$ / image== How to set up? 1. Accounts & APIs In the Edit Field "Setup" Node replace all ==[YOUR_API_TOKEN]== with your API Token : Fal.ai (gemini-25-flash-image/edit): https://fal.ai/models/fal-ai/gemini-25-flash-image/edit/api In Credentials on your n8n Dashboard, connect the following accounts using ==Client ID / Secret==: Google Drive: https://docs.n8n.io/integrations/builtin/credentials/google/ 2. Requirements Base Image of your Product preferably have a White Background Your Google Drive Folder and every Files it contains should be publicly available 3. Customizations Change the amount of total UGC Generated: In Generate Prompts → Message → "Your task is to generate 50" Modify the instructions to generate the UGC Prompts: In Generate Prompts → Message Change the amount of Base Image: In Generate Image → Body Parameters → JSON → image_urls Change the amount of UGC Generated per prompt: In Generate Image → Body Parameters → JSON → num_images Modify the Folder where UGC Generated are stored: In Upload File → Parent Folder

AI Background Removal Workflow This workflow automatically removes backgrounds from images stored in Airtable using the APImage API 🡥, then downloads and saves the processed images to Google Drive. Perfect for batch processing product photos, portraits, or any images that need clean, transparent backgrounds. The source (Airtable) and the storage (Google Drive) can be changed to any service or database you want/use. 🧩 Nodes Overview 1. Remove Background (Manual Trigger) This manual trigger starts the background removal process when clicked. Customization Options: Replace with Schedule Trigger for automatic daily/weekly processing Replace with Webhook Trigger to start via API calls Replace with File Trigger to process when new files are added 2. Get a Record (Airtable) Retrieves media files from your Airtable "Creatives Library" database. Connects to the "Media Files" table in your Airtable base Fetches records containing image thumbnails for processing Returns all matching records with their thumbnail URLs and metadata Required Airtable Structure: Table with image/attachment field (currently expects "Thumbnail" field) Optional fields: File Name, Media Type, Upload Date, File Size Customization Options: Replace with Google Sheets, Notion, or any database node Add filters to process only specific records Change to different tables with image URLs 3. Code (JavaScript Processing) Processes Airtable records and prepares thumbnail data for background removal. Extracts thumbnail URLs from each record Chooses best quality thumbnail (large > full > original) Creates clean filenames by removing special characters Adds processing metadata and timestamps Key Features: // Selects best thumbnail quality if (thumbnail.thumbnails?.large?.url) { thumbnailUrl = thumbnail.thumbnails.large.url; } // Creates clean filename cleanFileName: (record.fields['File Name'] || 'unknown') .replace(//g, '_') .toLowerCase() Easy Customization for Different Databases: Product Database**: Change field mappings to 'Product Name', 'SKU', 'Category' Portfolio Database**: Use 'Project Name', 'Client', 'Tags' Employee Database**: Use 'Full Name', 'Department', 'Position' 4. Split Out Converts the array of thumbnails into individual items for parallel processing. Enables processing multiple images simultaneously Each item contains all thumbnail metadata for downstream nodes 5. APImage API (HTTP Request) Calls the APImage service to remove backgrounds from images. API Endpoint: POST https://apimage.org/api/ai-remove-background Request Configuration: Header**: Authorization: Bearer YOUR_API_KEY Body**: image_url: {{ $json.originalThumbnailUrl }} ✅ Setup Required: Replace YOUR_API_KEY with your actual API key Get your key from APImage Dashboard 🡥 6. Download (HTTP Request) Downloads the processed image from APImage's servers using the returned URL. Fetches the background-removed image file Prepares image data for upload to storage 7. Upload File (Google Drive) Saves processed images to your Google Drive in a "bg_removal" folder. Customization Options: Replace with Dropbox, OneDrive, AWS S3, or FTP upload Create date-based folder structures Use dynamic filenames with metadata Upload to multiple destinations simultaneously ✨ How To Get Started Set up APImage API: Double-click the APImage API node Replace YOUR_API_KEY with your actual API key Keep the Bearer prefix Configure Airtable: Ensure your Airtable has a table with image attachments Update field names in the Code node if different from defaults Test the workflow: Click the Remove Background trigger node Verify images are processed and uploaded successfully 🔗 Get your API Key 🡥 🔧 How to Customize Input Customization (Left Section) Replace the Airtable integration with any data source containing image URLs: Google Sheets** with product catalogs Notion** databases with image galleries Webhooks** from external systems File system** monitoring for new uploads Database** queries for image records Output Customization (Right Section) Modify where processed images are stored: Multiple Storage**: Upload to Google Drive + Dropbox simultaneously Database Updates**: Update original records with processed image URLs Email/Slack**: Send processed images via communication tools Website Integration**: Upload directly to WordPress, Shopify, etc. Processing Customization Batch Processing**: Limit concurrent API calls Quality Control**: Add image validation before/after processing Format Conversion**: Use Sharp node for resizing or format changes Metadata Preservation**: Extract and maintain EXIF data 📋 Workflow Connections Remove Background → Get a Record → Code → Split Out → APImage API → Download → Upload File 🎯 Perfect For E-commerce**: Batch process product photos for clean, professional listings Marketing Teams**: Remove backgrounds from brand assets and imagery Photographers**: Automate background removal for portrait sessions Content Creators**: Prepare images for presentations and social media Design Agencies**: Streamline asset preparation workflows 📚 Resources APImage API Documentation 🡥 Airtable API Reference 🡥 n8n Documentation 🡥 ⚡ Processing Speed: Handles multiple images in parallel for fast batch processing 🔒 Secure: API keys stored safely in n8n credentials 🔄 Reliable: Built-in error handling and retry mechanisms

Description 🎯 Overview An advanced automated trading bot that implements ICT (Inner Circle Trader) methodology and Smart Money Concepts for cryptocurrency trading. This workflow combines AI-powered market analysis with automated trade execution through Coinbase Advanced Trading API. ⚡ Key Features 📊 ICT Trading Strategy Implementation Kill Zone Detection**: Automatically identifies optimal trading sessions (Asian, London, New York kill zones) Smart Money Concepts**: Analyzes market structure breaks, liquidity grabs, fair value gaps, and order blocks Session Validation**: Real-time GMT time tracking with session strength calculations Structure Analysis**: Detects BOS (Break of Structure) and CHOCH (Change of Character) patterns 🤖 AI-Powered Analysis GPT-4 Integration**: Advanced market analysis using OpenAI's latest model Confidence Scoring**: AI generates confidence scores (0-100) for each trading signal Risk Assessment**: Automated risk level evaluation (LOW/MEDIUM/HIGH) ICT-Specific Prompts**: Custom prompts designed for Inner Circle Trader methodology 🔄 Automated Trading Flow Signal Reception: Receives trading signals via Telegram webhook Data Extraction: Parses symbol, action, price, and technical indicators Session Validation: Verifies current kill zone and trading session strength Market Data: Fetches real-time data from Coinbase Advanced Trading API AI Analysis: Processes signals through GPT-4 with ICT-specific analysis Quality Filter: Multi-condition filtering based on confidence, session, and structure Trade Execution: Automated order placement through Coinbase API Documentation: Records all trades and rejections in Notion databases 📱 Multi-Platform Integration Telegram Bot**: Receives signals and sends formatted notifications Coinbase Advanced**: Real-time market data and trade execution Notion Database**: Comprehensive trade logging and analysis tracking Webhook Support**: External system integration capabilities 🛠️ Setup Requirements API Credentials Needed: Coinbase Advanced Trading API** (API Key, Secret, Passphrase) OpenAI API Key** (GPT-4 access) Telegram Bot Token** and Chat ID Notion Integration** (Database IDs for trade records) Environment Variables: TELEGRAM_CHAT_ID=your_chat_id NOTION_TRADING_DB_ID=your_trading_database_id NOTION_REJECTED_DB_ID=your_rejected_signals_database_id WEBHOOK_URL=your_external_webhook_url 📈 Trading Logic Kill Zone Priority System: London & New York Sessions**: HIGH priority (0.9 strength) Asian & London Close**: MEDIUM priority (0.6 strength) Off Hours**: LOW priority (0.1 strength) Signal Validation Criteria: Signal quality must not be "LOW" Confidence score ≥ 60% Active kill zone session required ICT structure alignment confirmed 🎛️ Workflow Components Extract ICT Signal Data: Parses incoming Telegram messages for trading signals ICT Session Validator: Determines current kill zone and session strength Get Coinbase Market Data: Fetches real-time cryptocurrency data ICT AI Analysis: GPT-4 powered analysis with ICT methodology Parse ICT AI Analysis: Processes AI response with fallback mechanisms ICT Quality & Session Filter: Multi-condition signal validation Execute ICT Trade: Automated trade execution via Coinbase API Create ICT Trading Record: Logs successful trades to Notion Generate ICT Notification: Creates formatted Telegram alerts Log ICT Rejected Signal: Records filtered signals for analysis 🚀 Use Cases Automated ICT-based cryptocurrency trading Smart Money Concepts implementation Kill zone session trading AI-enhanced market structure analysis Professional trading documentation and tracking ⚠️ Risk Management Built-in session validation prevents off-hours trading AI confidence scoring filters low-quality signals Comprehensive logging for performance analysis Automated stop-loss and take-profit calculations This workflow is perfect for traders familiar with ICT methodology who want to automate their Smart Money Concepts trading strategy with AI-enhanced decision making.

Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team Trigger When chat message received → User submits an SEO request (e.g., “Help me rank for project management software”). The message goes straight to the SEO Director Agent. SEO Director Agent (O3) Acts like the head of SEO strategy. Uses the Think node to plan and decide which specialists to call. Delegates tasks to relevant agents. Specialist Agents (GPT-4.1-mini) Each agent has its own OpenAI model connection for lightweight cost-efficient execution. Tasks include: Keyword Research Specialist → Keyword discovery, clustering, competitor analysis. SEO Content Writer → Generates optimized blog posts, landing pages, etc. Technical SEO Specialist → Site audit, schema markup, crawling fixes. Link Building Strategist → Backlink strategies, outreach campaign ideas. Local SEO Specialist → Local citations, GMB optimization, geo-content. Analytics Specialist → Reports, performance insights, ranking metrics. Feedback Loop Each agent sends results back to the SEO Director. Director compiles insights into a comprehensive SEO campaign plan. ✅ Why This Setup Works Well O3 Model for Director** → Handles reasoning-heavy orchestration (strategy, delegation). GPT-4.1-mini for Specialists** → Cheap, fast, task-specific execution. Parallel Execution** → All specialists can run at the same time. Scalable & Modular** → You can add/remove agents depending on campaign needs. Sticky Notes** → Already document the workflow (great for onboarding & sharing).

How it works This workflow starts whenever a new domain is added to a Google Sheet. It cleans the domain, fetches traffic insights from SimilarWeb, extracts the most relevant metrics, and updates the sheet with enriched data. Optionally, it can also send this information to Airtable for further tracking or analysis. Step-by-step Trigger on New Domain Workflow starts when a new row is added in the Google Sheet. Captures the raw URL/domain entered by the user. Clean Domain URL Strips unnecessary parts like http://, https://, www., and trailing slashes. Stores a clean domain format (e.g., example.com) along with the row number. Fetch Website Analysis Uses the SimilarWeb API to pull traffic and engagement insights for the domain. Data includes global rank, country rank, category rank, total visits, bounce rate, and more. Extract Key Metrics Processes raw SimilarWeb data into a simplified structure. Extracted insights include: Ranks: Global, Country, and Category. Traffic Overview: Total Visits, Bounce Rate, Pages per Visit, Avg Visit Duration. Top Traffic Sources: Direct, Search, Social. Top Countries (Top 3): With traffic share percentages. Device Split: Mobile vs Desktop. Update Google Sheet Writes the cleaned and enriched domain data back into the same (or another) Google Sheet. Ensures each row is updated with the new traffic insights. Export to Airtable (Optional) Creates a new record in Airtable with the enriched traffic metrics. Useful if you want to manage or visualize company/domain data outside of Google Sheets. Why use this? Automatically enriches domain lists with live traffic data from SimilarWeb. Cleans messy URLs into a standard format. Saves hours of manual research on company traffic insights. Provides structured, comparable metrics for better decision-making. Flexible: update sheets, export to Airtable, or both.

Amazon Luna Prime Games Catalog Tracker (Auto-Sync to Google Sheets)** Automatically fetch, organize, and maintain an updated catalog of Amazon Luna – Included with Prime games.This workflow regularly queries Amazon’s official Luna endpoint, extracts complete metadata, and syncs everything into Google Sheets without duplicates. Ideal for: tracking monthly Prime Luna rotations keeping a personal archive of games monitoring new games appearing on Amazon Games / Prime Gaming, so you can instantly play titles you’re interested in building dashboards or gaming databases powering notification systems (Discord, Telegram, email, etc.) Overview Amazon Luna’s “Included with Prime” lineup changes frequently, with new games added and old ones removed.Instead of checking manually, this n8n template fully automates the process: Fetches the latest list from Amazon’s backend Extracts detailed metadata from the response Syncs the data into Google Sheets Avoids duplicates by updating existing rows Supports all major Amazon regions Once configured, it runs automatically—keeping your game catalog correct, clean, and always up to date. 🛠️ How the workflow works 1. Scheduled Trigger Starts the workflow on a set schedule (default: every 5 days at 3:00 PM).You can change both frequency and time freely. 2. HTTP Request to Amazon Luna Calls Amazon Luna’s regional endpoint and retrieves the full “Included with Prime” catalog. 3. JavaScript Code Node – Data Extraction Parses the JSON response and extracts structured fields: Title Genres Release Year ASIN Image URLs Additional metadata The result is a clean, ready-to-use dataset. 4. Google Sheets – Insert or Update Rows Each game is written into the selected Google Sheet: Existing games get updated New games are appended The Title acts as the unique identifier to prevent duplicates. ## ⚙️ Configuration Parameters | Parameter | Description | Recommended values | | --- | --- | --- | | x-amz-locale | Language + region | it_IT 🇮🇹 · en_US 🇺🇸 · de_DE 🇩🇪 · fr_FR 🇫🇷 · es_ES 🇪🇸 · en_GB 🇬🇧 · ja_JP 🇯🇵 · en_CA 🇨🇦 | | x-amz-marketplace-id | Marketplace backend ID | APJ6JRA9NG5V4 🇮🇹 · ATVPDKIKX0DER 🇺🇸 · A1PA6795UKMFR9 🇩🇪 · A13V1IB3VIYZZH 🇫🇷 · A1RKKUPIHCS9HS 🇪🇸 · A1F83G8C2ARO7P 🇬🇧 · A1VC38T7YXB528 🇯🇵 · A2EUQ1WTGCTBG2 🇨🇦 | | Accept-Language | Response language | Example: it-IT,it;q=0.9,en;q=0.8 | | User-Agent | Browser-like request | Default or updated UA | | Trigger interval | Refresh frequency | Every 5 days at 3:00 PM (modifiable) | | Google Sheet | Storage output | Select your file + sheet | You can adapt these headers to fetch data from any supported country. 💡 Tips & Customization 🌍 Regional catalogs Duplicate the HTTP Request + Code + Sheet block to track multiple countries (US, DE, JP, UK…). 🧹 No duplicates The workflow updates rows intelligently, ensuring a clean catalog even after many runs. 🗂️ Move data anywhere Send the output to: Airtable Databases (MySQL, Postgres, MongoDB…) Notion CSV REST APIs BI dashboards 🔔 Add notifications (Discord, Telegram, Email, etc.) You can pair this template with a notification workflow.When used with Discord, the notification message can include: game title description or metadata the game’s image**, automatically downloaded and attached This makes notifications visually informative and perfect for tracking new Prime titles. 🔒 Important Notes All retrieved data belongs to Amazon. The workflow is intended for personal, testing, or educational use only. Do not republish or redistribute collected data without permission.

How it works This template helps project managers collect task updates and photo reports from field workers via Telegram and stores everything in a Google Sheet. It enables daily project reporting without paper or back-office overhead. High-level flow: Workers receive daily tasks via Telegram They respond with photo reports Bot auto-saves replies (photos + status) to a Google Sheet The system tracks task completion, adds timestamps, and maintains report history Set up steps 🕒 Estimated setup time: 15–30 min You’ll need: A Telegram bot (via BotFather) A connected Google Sheet (with specific column headers) A set of preconfigured tasks 👉 Detailed setup instructions and required table structure are documented in sticky notes inside the workflow. Consulting and Training We work with leading construction, engineering, consulting agencies and technology firms around the world to help them implement open data principles, automate CAD/BIM processing and build robust ETL pipelines. If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us. Docs & Issues: Full Readme on GitHub

Overview This n8n workflow creates an intelligent AI agent that automates browser interactions through Airtop's browser automation platform. The agent can control real browser sessions, navigate websites, interact with web elements, and maintain detailed session records - all while providing live viewing capabilities for real-time monitoring. Youtube Tutorial: https://www.youtube.com/watch?v=XoZqFY7QFps What This Workflow Does The AI agent acts as your virtual assistant in the browser, capable of: Session Management**: Creates, monitors, and terminates browser sessions with proper tracking Web Navigation**: Visits websites, clicks elements, fills forms, and performs complex interactions Multi-Window Support**: Manages multiple browser windows within sessions Live Monitoring**: Provides real-time viewing URLs so you can watch the automation Data Tracking**: Maintains comprehensive records of all browser activities Profile Integration**: Uses Airtop profiles for authenticated sessions Email Notifications**: Sends live URLs and status updates via Gmail Demo Use Case: Automated Reddit Posting The tutorial demonstrates the agent's capabilities by: Logging into Reddit using pre-configured Airtop profile credentials Navigating to a specific subreddit based on user input Creating and publishing a new post with title and content Tracking the entire process with detailed session records Providing live viewing access throughout the automation Core Workflow Components 1. Chat Interface Trigger Node Type**: Chat Trigger Purpose**: Accepts user commands for browser automation tasks Input**: Natural language instructions (e.g., "Create a Reddit post in r/automation") 2. AI Agent Processing Node Type**: OpenAI GPT-4 Purpose**: Interprets user requests and determines appropriate browser actions System Message**: Contains the comprehensive agent instructions from your documentation Capabilities**: Understands complex web interaction requests Plans multi-step browser workflows Manages session states intelligently Handles error scenarios gracefully 3. Google Sheets Data Management Multiple Google Sheets nodes manage different aspects of session tracking: Browser Sessions Sheet Fields**: session_id, description, status, created_date Purpose**: Tracks active browser sessions Operations**: Create, read, update session records Window Sessions Sheet Fields**: session_id, window_id, description, airtop_live_view_url, status Purpose**: Tracks individual browser windows within sessions Operations**: Create, read, update window records Airtop Profiles Sheet Fields**: platform_name, platform_url, profile_name Purpose**: Stores available authenticated profiles Operations**: Read available profiles for session creation 4. Airtop Browser Automation Nodes Multiple specialized nodes for browser control: Session Management create_session**: Creates new browser sessions with optional profile authentication terminate_session**: Closes browser sessions and updates records read_airtop_profiles**: Retrieves available authentication profiles Window Management create_window**: Opens new browser windows with specified URLs query_page**: Analyzes page content and identifies interactive elements Web Interaction click_element**: Clicks specific page elements based on AI descriptions type_text**: Inputs text into form fields and input elements 5. Gmail Integration Node Type**: Gmail Send Purpose**: Sends live viewing URLs and status updates Recipients**: User email for real-time monitoring Content**: Complete Airtop live view URLs for browser session observation 6. Error Handling & Validation Input Validation**: Ensures required parameters are present Session State Checks**: Verifies browser session status before operations Error Recovery**: Handles failed operations gracefully Data Consistency**: Maintains accurate session records even during failures Technical Requirements API Credentials Needed Airtop.ai API Key Sign up at airtop.ai Generate API key from dashboard Required for all browser automation functions OpenAI API Key OpenAI account with GPT-4 access Required for AI agent intelligence and decision-making Google Sheets Access Google account with Google Sheets API access Copy the provided template and get your sheet URL Required for session and profile data management Gmail OAuth Google account with Gmail API access Required for sending live viewing URLs and notifications Airtable Base Structure Create three tables in your Airtable base: 1. Browser Details (Sessions) session_id (Single line text) description (Single line text) status (Single select: Open, Closed) created_date (Date) 2. Window Details (Windows) session_id (Single line text) window_id (Single line text) description (Single line text) airtop_live_view_url (URL) status (Single select: Open, Closed) 3. Airtop Profiles platform_name (Single line text) platform_url (URL) profile_name (Single line text) Workflow Logic Flow User Request Processing User Input: Natural language command via chat interface AI Analysis: OpenAI processes request and determines required actions Session Check: Agent reads current browser session status Action Planning: AI creates step-by-step execution plan Browser Session Lifecycle Session Creation: Check for existing open sessions Ask user about profile usage if needed Create new Airtop session Record session details in Airtable Window Management: Create browser window with target URL Capture live viewing URL Record window details in Airtable Send live URL via Gmail Web Interactions: Query page content for element identification Execute clicks, form fills, navigation Monitor page state changes Handle dynamic content loading Session Cleanup: Terminate browser session when complete Update all related records to "Closed" status Send completion notification Data Flow Architecture User Input → AI Processing → Session Management → Browser Actions → Data Recording → User Notifications Key Features & Benefits Intelligent Automation Natural Language Control**: Users can describe tasks in plain English Context Awareness**: AI understands complex multi-step workflows Adaptive Responses**: Handles unexpected page changes and errors Profile Integration**: Seamlessly uses stored authentication credentials Real-Time Monitoring Live View URLs**: Watch browser automation as it happens Status Updates**: Real-time notifications of task progress Session Tracking**: Complete audit trail of all browser activities Multi-Window Support**: Handle complex workflows across multiple tabs Enterprise-Ready Features Error Recovery**: Robust handling of network issues and page failures Session Persistence**: Maintains state across workflow interruptions Data Integrity**: Consistent record-keeping even during failures Scalable Architecture**: Can handle multiple concurrent automation tasks Use Cases Beyond Reddit This workflow architecture supports automation for any website: Social Media Management Multi-platform posting**: Facebook, Twitter, LinkedIn, Instagram Community engagement**: Responding to comments, messages Content scheduling**: Publishing posts at optimal times Analytics gathering**: Collecting engagement metrics Business Process Automation CRM data entry**: Updating customer records across platforms Support ticket management**: Creating, updating, routing tickets E-commerce operations**: Product listings, inventory updates Report generation**: Gathering data from multiple web sources Personal Productivity Travel booking**: Comparing prices, making reservations Bill management**: Paying utilities, checking statements Job applications**: Submitting applications, tracking status Research tasks**: Gathering information from multiple sources Advanced Configuration Options Custom Profiles Create Airtop profiles for different websites Store authentication credentials securely Switch between different user accounts Handle multi-factor authentication flows Workflow Customization Modify AI system prompts for specific use cases Add custom validation rules Implement retry logic for failed operations Create domain-specific interaction patterns Integration Extensions Connect to additional data sources Add webhook notifications Implement approval workflows Create audit logs and reporting Getting Started 📊 Copy the Google Sheets Template - Just click and make a copy! Set up credentials for Airtop, OpenAI, and Gmail Import workflow into your n8n instance Configure node credentials with your API keys and Google Sheets URL Test with simple commands like "Visit google.com" Expand to complex workflows as you become comfortable Best Practices Session Management Always check for existing sessions before creating new ones Properly terminate sessions to avoid resource waste Use descriptive names for sessions and windows Regularly clean up old session records Error Handling Implement timeout handling for slow-loading pages Add retry logic for network failures Validate element existence before interactions Log detailed error information for debugging Security Considerations Store sensitive credentials in Airtop profiles, not workflow Use webhook authentication for production deployments Implement rate limiting to avoid being blocked by websites Regular audit of browser session activities This workflow transforms n8n into a powerful browser automation platform, enabling you to automate virtually any web-based task while maintaining full visibility and control over the automation process.

Automatically Classify Support Tickets in Zoho Desk with AI with Gemini Transform your customer support workflow with intelligent ticket classification. This automation leverages AI to automatically categorize incoming support tickets in Zoho Desk, reducing manual work and ensuring faster ticket routing to the right teams. How It Works Fetches all tickets from Zoho Desk with pagination support Filters unclassified tickets (where classification field is null) Retrieves complete ticket threads for full conversation context Uses OpenRouter AI (GPT-4, Claude, or other models) to classify tickets into predefined categories Updates tickets in Zoho Desk with accurate classifications automatically Use Cases Customer Support Teams**: Automatically route tickets to specialized departments (billing, technical, sales) Help Desks**: Prioritize urgent issues and categorize feature requests Prerequisites Active Zoho Desk account with API access OpenRouter API account (supports multiple AI models) Basic understanding of OAuth2 authentication Predefined ticket categories in your Zoho Desk setup Setup Steps Time: ~15 minutes Configure Zoho Desk OAuth2 - Follow our step-by-step GitHub guide for OAuth2 credential setup Set up OpenRouter API - Create an account and generate API keys at openrouter.ai Customize classifications - Define your ticket categories (e.g., Technical, Billing, Feature Request, Bug Report) Adapt the workflow - Modify for any field: status, priority, tags, assignment, or custom fields Review API documentation - Check Zoho Desk Search API docs for advanced filtering options Test thoroughly - Run manual triggers before automation Note: This workflow demonstrates proper Zoho Desk API integration, including OAuth2 authentication and pagination handling—two common integration challenges.