Loading page
How it works This template launches your very first AI Agent —an AI-powered chatbot that can do more than just talk— it can take action using tools. Think of an AI Agent as a smart assistant, and the tools are the apps on its phone. By connecting it to other nodes, you give your agent the ability to interact with real-world data and services, like checking the weather, fetching news, or even sending emails on your behalf. This workflow is designed to be the perfect starting point: The Chat Interface: A Chat Trigger node provides a simple, clean interface for you to talk to your agent. The Brains: The AI Agent node receives your messages, intelligently decides which tool to use (if any), and formulates a helpful response. Its personality and instructions are fully customizable in the "System Message". The Language Model: It uses Google Gemini to power its reasoning and conversation skills. The Tools: It comes pre-equipped with two tools to demonstrate its capabilities: 1. Get Weather: Fetches real-time weather forecasts. 2. Get News: Reads any RSS feed to get the latest headlines. The Memory: A Conversation Memory node allows the agent to remember the last few messages, enabling natural, follow-up conversations. Set up steps Setup time: ~2 minutes You only need one thing to get started: a free Google AI API key. 1. Get Your Google AI API Key: Visit Google AI Studio at aistudio.google.com/app/apikey. Click "Create API key in new project" and copy the key that appears. 2. Add Your Credential in n8n: On the workflow canvas, go to the Connect your model (Google Gemini) node. Click the Credential dropdown and select + Create New Credential. Paste your API key into the API Key field and click Save. 3. Start Chatting! Go to the Example Chat node. Click the "Open Chat" button in its parameter panel. Try asking it one of the example questions, like: "What's the weather in Paris?" or "Get me the latest tech news."* That's it! You now have a fully functional AI Agent. Try adding more tools (like Gmail or Google Calendar) to make it even more powerful.
by Lucas PeyrinGenerate AI videos with Seedance & Blotato, upload to TikTok, YouTube & Instagram Who is this for? This template is ideal for creators, content marketers, social media managers, and AI enthusiasts who want to automate the production of short-form, visually captivating videos for platforms like TikTok, YouTube Shorts, and Instagram Reels — all without manual editing or publishing. What problem is this workflow solving? Creating engaging videos requires: Generating creative ideas Writing detailed scene prompts Producing realistic video clips and sound effects Editing and stitching the final video Publishing across multiple platforms This workflow automates the entire process, saving hours of manual work and ensuring consistent, AI-driven content output ready for social distribution. What this workflow does This end-to-end AI video automation workflow: 1. Generates a creative idea using OpenAI and LangChain 2. Creates detailed video prompts with Seedance AI 3. Generates video clips via Wavespeed AI 4. Generates sound effects with Fal AI 5. Stitches the final video using Fal AI’s ffmpeg API 6. Logs metadata and video links to Google Sheets 7. Uploads the video to Blotato 8. Auto-publishes to TikTok, YouTube, Instagram, and other platforms Setup 1. Add your OpenAI API key in the LLM nodes 2. Set up Seedance and Wavespeed AI credentials for video prompt and clip generation 3. Add your Fal AI API key for sound and stitching steps 4. Connect your Google Sheets account for tracking ideas and outputs 5. Set your Blotato API key and fill in the platform account IDs in the Assign Social Media IDs node 6. Adjust the Schedule Trigger to control when the automation runs How to customize this workflow to your needs Change the AI prompts to target your niche (e.g., ASMR, product videos, humor) Add a Telegram or Slack step for video preview before publishing Tweak scene structure or video duration to match your style Disable platforms you don’t want by turning off specific HTTP Request nodes Edit the sound generation prompts for different moods or effects Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
by Dr. FirasAutomate video creation with Veo3 and auto-post to Instagram, TikTok via Blotato Who is this for? This template is ideal for content creators, social media managers, YouTubers, and digital marketers who want to generate high-quality videos daily using AI and distribute them effortlessly across multiple platforms. It’s perfect for anyone who wants to scale short-form content creation without video editing tools. What problem is this workflow solving? Creating and distributing consistent video content requires: Generating ideas Writing scripts and prompts Rendering videos Manually posting to platforms This workflow automates all of that. It transforms one prompt into a professional AI-generated video and publishes it automatically — saving time and increasing reach. What this workflow does 1. Triggers daily to generate a new idea with OpenAI (or your custom prompt). 2. Creates a video prompt formatted specifically for Google Veo3. 3. Generates a cinematic video using the Veo3 API. 4. Logs the video data into a Google Sheet. 5. Retrieves the final video URL once Veo3 finishes rendering. 6. Uploads the video to Blotato for publishing. 7. Auto-posts the video to Instagram, TikTok, YouTube, Facebook, LinkedIn, Threads, Twitter (X), Pinterest, and Bluesky. Setup 1. Add your OpenAI API key to the GPT-4.1 nodes. 2. Connect your Veo3 API credentials in the video generation node. 3. Link your Google Sheets account and use a sheet with columns: Prompt, Video URL, Status. 4. Connect your Blotato API key and set your platform IDs in the Assign Social Media IDs node. 5. Adjust the Schedule Trigger to your desired posting frequency. How to customize this workflow to your needs Edit the AI prompt to align with your niche (fitness, finance, education, etc.). Add your own branding overlays using JSON2Video or similar tools. Change platform selection by enabling/disabling specific HTTP Request nodes. Add a Telegram step to preview the video before auto-posting. Track performance by adding metrics columns in Google Sheets. Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
by Dr. FirasWho is this for? This template is designed for internal support teams, product specialists, and knowledge managers in technology companies who want to automate ingestion of product documentation and enable AI-driven, retrieval-augmented question answering via WhatsApp. What problem is this workflow solving? Support agents often spend too much time manually searching through lengthy documentation, leading to inconsistent or delayed answers. This solution automates importing, chunking, and indexing product manuals, then uses retrieval-augmented generation (RAG) to answer user queries accurately and quickly with AI via WhatsApp messaging. What these workflows do Workflow 1: Document Ingestion & Indexing Manually triggered to import product documentation from Google Docs. Automatically splits large documents into chunks for efficient searching. Generates vector embeddings for each chunk using OpenAI embeddings. Inserts the embedded chunks and metadata into a MongoDB Atlas vector store, enabling fast semantic search. Workflow 2: AI-Powered Query & Response via WhatsApp Listens for incoming WhatsApp user messages, supporting various types: Text messages: Plain text queries from users. Audio messages: Voice notes transcribed into text for processing. Image messages: Photos or screenshots analyzed to provide contextual answers. Document messages: PDFs, spreadsheets, or other files parsed for relevant content. Converts incoming queries to vector embeddings and performs similarity search on the MongoDB vector store. Uses OpenAI’s GPT-4o-mini model with retrieval-augmented generation to produce concise, context-aware answers. Maintains conversation context across multiple turns using a memory buffer node. Routes different message types to appropriate processing nodes to maximize answer quality. Setup Setting up vector embeddings 1. Authenticate Google Docs and connect your Google Docs URL containing the product documentation you want to index. 2. Authenticate MongoDB Atlas and connect the collection where you want to store the vector embeddings. Create a search index on this collection to support vector similarity queries. 3. Ensure the index name matches the one configured in n8n (data_index). 4. See the example MongoDB search index template below for reference. Setting up chat 1. Authenticate the WhatsApp node with your Meta account credentials to enable message receiving and sending. 2. Connect the MongoDB collection containing embedded product documentation to the MongoDB Vector Search node used for similarity queries. 3. Set up the system prompt in the Knowledge Base Agent node to reflect your company’s tone, answering style, and any business rules, ensuring it references the connected MongoDB collection for context retrieval. Make sure Both MongoDB nodes (in ingestion and chat workflows) are connected to the same collection with: An embedding field storing vector data, Relevant metadata fields (e.g., document ID, source), and The same vector index name configured (e.g., data_index). Search Index Example: { "mappings": { "dynamic": false, "fields": { "_id": { "type": "string" }, "text": { "type": "string" }, "embedding": { "type": "knnVector", "dimensions": 1536, "similarity": "cosine" }, "source": { "type": "string" }, "doc_id": { "type": "string" } } } }
by NovaNode//ASMR AI Workflow Who is this for? Content Creators, YouTube Automation Enthusiasts, and AI Hobbyists looking to autonomously generate and publish unique, satisfying ASMR-style YouTube Shorts without manual effort. What problem does this solve? This workflow solves the creative bottleneck and time-consuming nature of daily content creation. It fully automates the entire production pipeline, from brainstorming trendy ideas to publishing a finished video, turning your n8n instance into a 24/7 content factory. What this workflow does 1. Two-Stage AI Ideation & Planning: Uses an initial AI agent to brainstorm a short, viral ASMR concept based on current trends. A second "Planning" AI agent then takes this concept and expands it into a detailed, structured production plan, complete with a viral-optimized caption, hashtags, and descriptions for the environment and sound. 2. Multi-Modal Asset Generation: Video: Feeds detailed scene prompts to the ByteDance Seedance text-to-video model (via Wavespeed AI) to generate high-quality video clips. Audio: Simultaneously calls the Fal AI text-to-audio model to create custom, soothing ASMR sound effects that match the video's theme. Assembly: Automatically sequences the video clips and sound into a single, cohesive final video file using an FFMPEG API call. 3. Closed-Loop Publishing & Logging: Logging: Initially logs the new idea to a Google Sheet with a status of "In Progress". Publishing: Automatically uploads the final, assembled video directly to your YouTube channel, setting the title and description from the AI's plan. Updating: Finds the original row in the Google Sheet and updates its status to "Done", adding a direct link to the newly published YouTube video. Notifications: Sends real-time alerts to Telegram and/or Gmail with the video title and link, confirming the successful publication. Setup Credentials: You will need to create credentials in your n8n instance for the following services: OpenAI API Wavespeed AI API (for Seedance) Fal AI API Google OAuth Credential (enable YouTube Data API v3 and Google Sheets API in your Google Cloud Project) Telegram Bot Credential (Optional) Gmail OAuth Credential Configuration: This is an advanced workflow. The initial setup should take approximately 15-20 minutes. Google Sheet: Create a Google Sheet with these columns: idea, caption, production_status, youtube_url. Add the Sheet ID to the Google Sheets nodes in the workflow. Node Configuration: In the Telegram Notification node, enter your own Chat ID. In the Gmail Notification node, update the recipient email address. Activate: Once configured, save and set the workflow to "Active" to let it run on its schedule. How to customize Creative Direction: To change the style or theme of the videos (e.g., from kinetic sand to soap cutting), simply edit the systemMessage in the "2. Enrich Idea into Plan" and "Prompts AI Agent" nodes. Initial Ideas: To influence the AI's starting concepts, modify the prompt in the "1. Generate Trendy Idea" node. Video & Sound: To change the video duration or sound style, adjust the parameters in the "Create Clips" and "Create Sounds" nodes. Notifications: Add or remove notification channels (like Slack or Discord) after the "Upload to YouTube" node.
by Bilel ArouaHow it works Automatically generates trending LinkedIn content topics using AI Researches current industry angles and hooks Writes posts in your authentic voice using OpenAI Creates professional images with DALL-E Posts everything on schedule without manual intervention Set up steps Connect OpenAI API for content generation and image creation Link LinkedIn API for automated posting Configure scheduling triggers (daily/weekly posting) Customize prompts to match your writing style and industry Set up content approval workflows (optional) Results you can expect 400% increase in profile views within 3 weeks Generate 120+ posts per month vs manual 12 posts Free up 15+ hours weekly for revenue-generating activities Consistent posting schedule that builds audience engagement Professional content that converts followers to clients Time to set up: 30-45 minutes Technical level: Beginner to intermediate APIs required: OpenAI, LinkedIn API Cost: OpenAI usage fees only (approximately $5-15/month) This workflow transforms LinkedIn content creation from a time-consuming daily task into a fully automated system that works while you sleep. Perfect for entrepreneurs, marketers, and content creators who want consistent LinkedIn presence without the manual effort.
by Samuel KimutaiThis n8n workflow template creates an intelligent data analysis chatbot that can answer questions about data stored in Google Sheets using OpenAI's GPT-5 Mini model. The system automatically analyzes your spreadsheet data and provides insights through natural language conversations. What This Workflow Does Chat Interface: Provides a conversational interface for asking questions about your data Smart Data Analysis: Uses AI to understand column structures and data relationships Google Sheets Integration: Connects directly to your Google Sheets data Memory Buffer: Maintains conversation context for follow-up questions Automated Column Detection: Automatically identifies and describes your data columns Try It Out! --- 1. Set Up OpenAI Connection Get Your API Key 1. Visit the OpenAI API Keys page. 2. Go to OpenAI Billing. 3. Add funds to your billing account. 4. Copy your API key into your OpenAI credentials in n8n (or your chosen platform). --- 2. Prepare Your Google Sheet Connect Your Data in Google Sheets Data must follow this format: Sample Marketing Data First row contains column names. Data should be in rows 2–100. Log in using OAuth, then select your workbook and sheet. --- 3. Ask Questions of Your Data You can ask natural language questions to analyze your marketing data, such as: Total spend across all campaigns. Spend for Paid Search only. Month-over-month changes in ad spend. Top-performing campaigns by conversion rate. Cost per lead for each channel. --- Need Help or Want to Customize This? rbreen@ynteractive.com LinkedIn n8n Automation Experts
by Robert BreenDocument-Aware WhatsApp AI Bot for Customer Support Google Docs-Powered WhatsApp Support Agent 24/7 WhatsApp AI Assistant with Live Knowledge from Google Docs Description Template Smart WhatsApp AI Assistant Using Google Docs Help customers instantly on WhatsApp using a smart AI assistant that reads your company’s internal knowledge from a Google Doc in real time. Built for clubs, restaurants, agencies, or any business where clients ask questions based on a policy, FAQ, or services document. How it works Users send free-form questions to your WhatsApp Business number (e.g. “What are the gym rules?” or “Are you open today?”) The bot automatically reads your company’s internal Google Doc (policy, schedule, etc.) It merges the document content with today’s date and the user’s question to craft a custom AI prompt The AI (Gemini or ChatGPT) then replies back on WhatsApp using natural, helpful language All conversations are logged to Google Sheets for reporting or audit > Bonus: The AI even understands dates inside the document and compares them to today’s date — e.g. if your document says “Closed May 25 for 30 days,” it will say “We're currently closed until June 24. Set up steps 1. Connect your WhatsApp Cloud API account (Meta) 2. Add your Google account and grant access to the Doc containing your company info 3. Choose your AI model (ChatGPT/OpenAI or Gemini) 4. Paste your document ID into the Google Docs node 5. Connect your WhatsApp webhook to Meta (only takes 5 minutes) 6. Done — start receiving and answering customer questions! > Works best with free-tier OpenAI/Gemini, Google Docs, and Meta's Cloud API (no phone required). Everything is modular, extensible, and low-code. Customization Tips Change the Google Doc anytime to update answers — no retraining needed Add your logo and business name in the AI agent’s “System Prompt” Add fallback routes like “Escalate to human” if the bot can't help Clone for multiple brands by duplicating the workflow and swapping in new docs Need Help Setting It Up? If you'd like help connecting your WhatsApp Business API, setting up Google Docs access, or customizing this AI assistant for your business or clients… I offer setup, branding, and customization services: WhatsApp Cloud API setup & verification Google OAuth & Doc structure guidance AI model configuration (OpenAI / Gemini) Branding & prompt tone customization Logging, reporting, and escalation logic Just send a message via: Email: tharwat.elsayed2000@gmail.com WhatsApp: +20 106 180 3236
by Tharwat MohamedBuild a 100% local RAG with n8n, Ollama and Qdrant. This agent uses a semantic database (Qdrant) to answer questions about PDF files. Tutorial Click here to view the YouTube Tutorial How it works Build a chatbot that answers based on documents you provide it (Retrieval Augmented Generation). You can upload as many PDF files as you want to the Qdrant database. The chatbot will use its retrieval tool to fetch the chunks and use them to answer questions. Installation 1. Install n8n + Ollama + Qdrant using the Self-hosted AI starter kit 2. Make sure to install Llama 3.2 and mxbai-embed-large as embeddings model. How to use it 1. First run the "Data Ingestion" part and upload as many PDF files as you want 2. Run the Chatbot and start asking questions about the documents you uploaded
by Thomas JanssenThis template quickly shows how to use RAG in n8n. Who is this for? This template is for everyone who wants to start giving knowledge to their Agents through RAG. Requirements Have a PDF with custom knowledge that you want to provide to your agent. Setup No setup required. Just hit Execute Workflow, upload your knowledge document and then start chatting. How to customize this to your needs 1. Add custom instructions to your Agent by changing the prompts in it. 2. Add a different way to load in knowledge to your vector store, e.g. by looking at some Google Drive files or loading knowledge from a table. 2. Exchange the Simple Vector Store nodes with your own vector store tools ready for production. 3. Add a more sophisticated way to rank files found in the vector store. For more information read our docs on RAG in n8n.
by n8n TeamWant to check out all my flows, follow me on: https://maxmitcham.substack.com/ https://www.linkedin.com/in/max-mitcham/ Email Manager - Intelligent Gmail Classification This automation flow is designed to automatically monitor incoming Gmail messages, analyze their content and context using AI, and intelligently classify them with appropriate labels for better email organization and prioritization. How It Works (Step-by-Step): 1. Gmail Monitoring (Trigger) Continuously monitors your Gmail inbox: `` Polls for new emails every minute Captures all incoming messages automatically Triggers workflow for each new email received ` 2. Email Content Extraction Retrieves complete email details: ` Full email body and headers Sender information and recipient lists Subject line and metadata Existing Gmail labels and categories Email threading information (replies/forwards) ` 3. Email History Analysis AI agent checks relationship context: ` Searches for previous emails from the same sender Checks sent folder for prior outbound correspondence Determines if this is a first-time contact (cold email) Analyzes conversation thread history ` 4. Intelligent Classification Agent Advanced AI categorization using: ` Claude Sonnet 4 for sophisticated email analysis Context-aware classification based on email history Content analysis for intent and urgency detection Header analysis for automated vs. human-sent emails ` 5. Smart Label Assignment Automatically applies appropriate Gmail labels: ` To Respond: Requires direct action/reply FYI: For awareness, no action needed Notification: Service updates, policy changes Marketing: Promotional content and sales pitches Meeting Update: Calendar-related communications Comment: Document/task feedback ` 6. Structured Processing Ensures consistent labeling: ` Uses structured output parsing for reliability Returns specific Label ID for Gmail integration Applies label automatically to the email Maintains classification accuracy ` Tools Used: ` n8n: Workflow automation platform Gmail API: Email monitoring and label management Anthropic Claude: Advanced email content analysis Gmail Tools: Email history checking and search Structured Output Parser: Consistent AI responses ` Key Features: ` Real-time email monitoring and classification Context-aware analysis using email history Intelligent cold vs. warm email detection Multiple classification categories for organization Automatic Gmail label application Header analysis for automated email detection Thread-aware conversation tracking ` Ideal Use Cases: ` Busy executives managing high email volumes Sales professionals prioritizing prospect communications Support teams organizing customer inquiries Marketing teams filtering promotional content Anyone wanting automated email organization Teams needing consistent email prioritization ``
by Max MitchamHow it works This template is a complete, hands-on tutorial that lets you build and interact with your very first AI Agent. Think of an AI Agent as a standard AI chatbot with superpowers. The agent doesn't just talk; it can use tools to perform actions and find information in real-time. This workflow is designed to show you exactly how that works. 1. The Chat Interface (Chat Trigger): This is your window to the agent. It's a fully styled, public-facing chat window where you can have a conversation. 2. The Brain (AI Agent Node): This is the core of the operation. It takes your message, understands your intent, and intelligently decides which "superpower" (or tool) it needs to use to answer your request. The agent's personality and instructions are defined in its extensive system prompt. 3. The Tools (Tool Nodes): These are the agent's superpowers. We've included a variety of useful and fun tools to showcase its capabilities: Get a random joke. Search Wikipedia for a summary of any topic. Calculate a future date. Generate a secure password. Calculate a monthly loan payment. Fetch the latest articles from the n8n blog. 4. The Memory (Memory Node): This gives the agent a short-term memory, allowing it to remember the last few messages in your conversation for better context. When you send a message, the agent's brain analyzes it, picks the right tool for the job, executes it, and then formulates a helpful response based on the tool's output. Set up steps Setup time: ~3 minutes This template is nearly ready to go out of the box. You just need to provide the AI's "brain." 1. Configure Credentials: This workflow requires an API key for an AI model. Make sure you have credentials set up in your n8n instance for either Google AI (Gemini) or OpenAI. 2. Choose Your AI Brain (LLM): By default, the workflow uses the Google Gemini node. If you have Google AI credentials, you're all set! If you prefer to use OpenAI, simply disable the Gemini node and enable the OpenAI node. You only need one active LLM node. Make sure it is connected to the Agent parent node. 3. Explore the Tools: Take a moment to look at the different tool nodes connected to the Your First AI Agent node. This is where the agent gets its abilities! You can add, remove, or modify these to create your own custom agent. 4. Activate and Test! Activate the workflow. Open the public URL for the Example Chat Window node (you can copy it from the node's panel). Start chatting! Try asking it things like: "Tell me a joke." "What is n8n?" "Generate a 16-character password for me." "What are the latest posts on the n8n blog?" "What is the monthly payment for a $300,000 loan at 5% interest over 30 years?"
by Lucas PeyrinCreate AI Viral Videos using NanoBanana 2 PRO & VEO3.1 and Publish via Blotato Who is this for? This template is for content creators, marketers, agencies, and UGC studios who want to turn a simple Telegram message into AI-generated vertical videos, automatically published across multiple social platforms using Blotato. --- What problem is this workflow solving? / Use case Creating short-form video ads usually requires: Designing visuals Writing hooks and captions Generating or editing video Manually uploading to TikTok, Instagram, YouTube, Facebook, LinkedIn, X, etc. This workflow solves that by automating the full pipeline from image + idea → edited image → AI video → multi-platform post. --- What this workflow does 1. Create Image with NanoBanana 2 PRO User sends a photo + caption idea to a Telegram bot. OpenAI Vision analyzes the reference image. An LLM builds a UGC-style image prompt. NanoBanana 2 PRO generates an enhanced, UGC-friendly image. 2. Generate Video with VEO3.1 An AI Agent structures a detailed Veo prompt (scene, camera, lighting, audio). Prompt is optimized and sent to VEO3.1 reference-to-video. The result is a 9:16, ~8s vertical video downloaded back into n8n. 3. Publish with Blotato Video is uploaded to Blotato. Posts are created for TikTok, Instagram, YouTube, Facebook, LinkedIn, and X using the AI-generated caption, title, and hashtags. A final “Published” message is sent on Telegram. --- Setup 1. Create and configure: Telegram bot (token in Set: Bot Token (Placeholder) node). OpenAI credentials. Fal.ai API key (for NanoBanana 2 PRO + VEO3.1). Blotato account + API credentials and connected social accounts. 2. Import the template into n8n and update all credential references. 3. Test by sending a product image + short idea to your Telegram bot. --- How to customize this workflow to your needs Edit the UGC image prompt system message to change visual style (more cinematic, minimal, etc.). Adjust the VEO prompt optimizer to tweak duration, mood, or camera movement. Enable/disable specific Blotato platforms depending on where you want to publish. Modify the caption/hashtag generation logic to match your brand tone, language, or niche. --- Need help or want to customize this? Contact: LinkedIn YouTube: @DRFIRASS Workshops: Mes Ateliers n8n --- Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube / Mes Ateliers n8n
by Dr. FirasThis workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors keyword rankings across search engines to track SEO performance and identify optimization opportunities. It saves you time by eliminating the need to manually check keyword positions and provides comprehensive ranking data for strategic SEO decision making. Overview This workflow automatically scrapes search engine results pages (SERPs) to track keyword rankings, competitor positions, and search features. It uses Bright Data to access search results without restrictions and AI to intelligently parse ranking data, track changes, and identify SEO opportunities. Tools Used n8n: The automation platform that orchestrates the workflow Bright Data: For scraping search engine results without being blocked OpenAI: AI agent for intelligent ranking analysis and SEO insights Google Sheets: For storing keyword ranking data and tracking changes How to Install 1. Import the Workflow: Download the .json file and import it into your n8n instance 2. Configure Bright Data: Add your Bright Data credentials to the MCP Client node 3. Set Up OpenAI: Configure your OpenAI API credentials 4. Configure Google Sheets: Connect your Google Sheets account and set up your ranking tracking spreadsheet 5. Customize: Define target keywords and ranking monitoring parameters Use Cases SEO Teams: Track keyword performance and identify ranking improvements Content Marketing: Monitor content ranking success and optimization needs Competitive Analysis: Track competitor keyword rankings and strategies Digital Marketing: Measure organic search performance and ROI Connect with Me Website: https://www.nofluff.online YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get Bright Data: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #keywordrankings #seo #searchrankings #brightdata #webscraping #seotools #n8nworkflow #workflow #nocode #ranktracking #keywordmonitoring #seoautomation #searchmarketing #organicseo #seoresearch #rankinganalysis #keywordanalysis #searchengines #seomonitoring #digitalmarketing #serp #keywordtracking #seoanalytics #searchoptimization #rankingreports #keywordresearch #seoinsights #searchperformance
by Yaron BeenWho’s it for This template is designed for anyone who wants to use Telegram as a personal AI assistant hub. If you often juggle tasks, emails, calendars, and expenses across multiple tools, this workflow consolidates everything into one seamless AI-powered agent. What it does Jarvis listens to your Telegram messages (text or audio) and processes them with OpenAI. Based on your request, it can: Manage tasks (create, complete, or delete) Handle calendar events (schedule, reschedule, or check availability) Send, draft, or fetch emails with Gmail Retrieve Google Contacts Log and track expenses All responses are returned directly to Telegram, giving you a unified command center. How to set up 1. Clone this template into your n8n workspace. 2. Connect your accounts (Telegram, Gmail, Google Calendar, Contacts, etc.). 3. Add your OpenAI API key in the Credentials section. 4. Test by sending a Telegram message like “Create a meeting tomorrow at 3pm” or “Add expense $50 for lunch.” or "Draft a reply with a project proposal to that email from Steve" Requirements n8n instance (cloud or self-hosted) Telegram Bot API credentials Gmail, Google Calendar, and Google Contacts credentials (optional, if using those features) OpenAI API key ElevenLabs API Key (optional, if you need audio note support) How to customize Swap Gmail with another email provider by replacing the Gmail MCP node. Add additional MCP integrations (e.g., Notion, Slack, CRM tools). Adjust memory length to control how much context Jarvis remembers. With this template, you can transform Telegram into your all-in-one AI assistant, simplifying workflows and saving hours every week.
by Jitesh DugarTelegram Nutrition AI Assistant (Alternative to Cal AI App) > AI-powered nutrition assistant for Telegram — log meals, set goals, and get personalized daily reports with Google Sheets integration. Description This n8n template creates a Telegram-based Nutrition AI Assistant designed as an open-source alternative to the Cal AI mobile app. It allows users to interact with an AI agent via text, voice, or images to track meals, calculate macros, and monitor nutrition goals directly from Telegram. The system integrates Google Sheets as the database, handling both user profiles and meal logs, while leveraging Gemini AI for natural conversation, food recognition, and daily progress reports. Key Features Multi-input support: Text, voice messages (transcribed), and food images (AI analysis). Macro calculation: Automatic estimation of calories, proteins, carbs, and fats. User-friendly registration: Simple onboarding without storing personal health data (no weight/height required). Goal tracking: Users can set and update calorie and protein targets. Daily reports: Personalized progress messages with visual progress bars. Google Sheets integration: Profile table for user targets. Meals table for food logs. Advanced n8n nodes: Includes use of Merge, Subworkflow, and Code nodes for data processing and report generation. Acknowledgment Inspired by the Cal AI concept — this template demonstrates how to reproduce its main functionality with n8n, Telegram, and AI agents as a flexible, open-source automation workflow. Tags telegram ai-assistant nutrition meal-tracking google-sheets food-logging voice-transcription image-analysis daily-reports n8n-template merge-node subworkflow-node code-node telegram-trigger google-gemini Use Case Use this template if you want to: Log meals using text, images, or voice messages. Track nutrition goals (calories, proteins) with daily progress updates. Provide a chat-based nutrition assistant without building a full app. Store structured nutrition data in Google Sheets for easy access and analysis. Example User Interactions User sends a photo of a meal → AI analyzes the food and logs calories/macros. User sends a voice message → AI transcribes and logs the meal. User types “report” → AI returns a daily nutrition summary with progress bars. User says “update my protein goal” → AI updates profile in Google Sheets. Required Credentials Telegram Bot API (Bot Token) Google Sheets API credentials AI Provider API (Google Gemini or compatible LLM) Setup Instructions 1. Create two Google Sheets tables: Profile: User_ID, Name, Calories_target, Protein_target Meals: User_ID, Date, Meal_description, Calories, Proteins, Carbs, Fats 2. Configure the Telegram Trigger with your bot token. 3. Connect your AI provider credentials (Gemini recommended). 4. Connect Google Sheets with your credentials. 5. ▶ Deploy the workflow in n8n. 6. Start interacting with your nutrition assistant via Telegram. Extra Notes Green section: Handles Telegram trigger and user check. Red section: Registers new users and sets goals. Blue section: Processes text, voice, and images. Yellow section: Generates nutrition reports. Purple section: Main AI agent controlling tools and logic. --- Need Assistance? If you’d like help customizing or extending this workflow, feel free to reach out: Email: johnsilva11031@gmail.com LinkedIn: John Alejandro Silva Rodríguez
by John Alejandro SIlvaGood to know: This workflow automatically processes incoming emails (you can filter them base on your needs) and creates concise AI-powered summaries, then logs them to a Google Sheets spreadsheet for easy tracking and analysis. Who is this for? Business professionals who receive many emails and need quick summaries Customer service teams tracking email communications Project managers monitoring email correspondence Anyone who wants to automatically organize and summarize their email communications What problem is this workflow solving? This workflow solves the problem of email overload by automatically reading incoming emails, generating concise summaries using AI, and organizing them in a structured format. It eliminates the need to manually read through every email to understand the key points and maintains a searchable record of communications. What this workflow does: Monitors your Gmail inbox for new emails Filters emails based on specific criteria (sender validation) Extracts key information (sender, date, subject, content) Uses AI to generate concise summaries of email content Automatically logs all data including the AI summary to a Google Sheets spreadsheet How it works: 1Gmail trigger monitors for new emails at specified intervals 2Email data is processed and formatted using JavaScript 3A conditional check validates the sender 4AI agent (powered by Groq's language model) reads the email content and generates a summary 5All information is automatically appended to a Google Sheets document How to use: Set up Gmail OAuth2 credentials in n8n Configure Google Sheets OAuth2 credentials Set up Groq API credentials for AI processing Create a Google Sheets document and update the document ID Customize the sender validation criteria as needed Activate the workflow Requirements: n8n instance (cloud or self-hosted) Gmail account with OAuth2 access Google Sheets account AI API Basic understanding of n8n workflow Customizing this workflow: Modify the Gmail trigger filters to target specific labels or criteria Adjust the sender validation logic in the conditional node Customize the AI prompt to change summary style or focus Add additional data fields to the Google Sheets output Change the polling frequency for checking new emails Switch to different AI models by replacing the Groq node
by ARREGenerate AI videos and carousels with Blotato and publish to Instagram & TikTok Documentation: Notion Guide Who is this for? This workflow is designed for content creators, marketers, solopreneurs, and automation enthusiasts who want to generate and publish short-form content on Instagram and TikTok automatically. It is ideal for users looking to combine AI-generated videos and carousels with Blotato and orchestrate everything using n8n. --- What this workflow does This workflow provides a complete end-to-end automation pipeline: 1. Receives a message from Telegram containing a public URL and a publishing instruction. 2. Creates a content source from the URL using Blotato. 3. Retrieves and validates the extracted text content. 4. Generates either: An AI tweet-card carousel for Instagram, or An AI-generated video for TikTok. 5. Continuously checks the visual generation status until it is fully completed. 6. Publishes the final media automatically to Instagram or TikTok. 7. Sends a confirmation message back to Telegram once the post is successfully published. --- Setup To use this workflow, you will need: An active n8n instance A Blotato account with API access Instagram and/or TikTok accounts connected in Blotato A Telegram Bot for triggering the workflow and receiving notifications Setup steps: 1. Import the workflow JSON into n8n. 2. Add your Blotato API credentials. 3. Configure the Telegram Trigger with your bot token. 4. Select your Instagram and TikTok accounts in the Blotato post nodes. 5. Activate the workflow. --- How to customize this workflow to your needs You can customize this workflow by: Changing the visual templates used in Blotato. Adjusting AI prompts to control tone, format, or content style. Adding additional publishing platforms after the posting step. Modifying polling behavior or adding timeouts for long visual renders. Replacing Telegram with another trigger such as Webhooks or Slack. The workflow is modular and easy to extend, making it suitable for a wide range of content automation use cases. Watch This Tutorial --- Need help or want to customize this? Contact: LinkedIn YouTube: @DRFIRASS Workshops: Mes Ateliers n8n Need help customizing? Contact me for consulting and support : Linkedin / Youtube / Mes Ateliers n8n
by Dr. FirasMaster Your First AI Email Agent with Smart Fallback! Welcome to your hands-on guide for building a resilient, intelligent email support system in n8n! This workflow is specifically designed as an educational tool to help you understand advanced AI automation concepts in a practical, easy-to-follow way. --- What You'll Learn & Build: This powerful template enables you to create an automated email support agent that: Monitors Gmail for new customer inquiries in real-time. Processes requests using a primary AI model (Google Gemini) for efficiency. Intelligently falls back to a secondary AI model (OpenAI GPT) if the primary model fails or for more complex queries, ensuring robust reliability. Generates personalized and helpful replies automatically. Logs every interaction meticulously to a Google Sheet for easy tracking and analysis. --- Why a Fallback Model is Game-Changing (and Why You Should Learn It): Unmatched Reliability (99.9% Uptime): If one AI service experiences an outage or rate limits, your automation seamlessly switches to another, ensuring no customer email goes unanswered. Cost Optimization: Leverage more affordable models (like Gemini) for standard queries, reserving premium models (like GPT) only when truly needed, significantly reducing your API costs. Superior Quality Assurance: Get the best of both worlds – the speed of cost-effective models combined with the accuracy of more powerful ones for complex scenarios. Real-World Application: This isn't just theory; it's a critical pattern for building resilient, production-ready AI systems. --- Perfect for Beginners & Aspiring Automators: Simple Setup: With drag-and-drop design and pre-built integrations, you can get this workflow running with minimal configuration. Just add your API keys! Clear Educational Value: Learn core concepts like AI model orchestration strategies, customer service automation best practices, and multi-model AI implementation patterns. Immediate Results: See your AI agent in action, responding to emails and logging data within minutes of setup. --- Getting Started Checklist: To use this workflow, you'll need: A Gmail account with API access enabled. A Google Sheets document created for logging. A Gemini API key (your primary AI model). An OpenAI API key (your fallback AI model). An n8n instance (cloud or desktop). --- Embark on your journey to building intelligent, resilient automation systems today!
by David OlusolaA hands-on starter workflow that teaches beginners how to: Pull rows from a Google Sheet Append a new record that mimics a form submission Generate AI-powered text with GPT-4o based on a “Topic” column Write the AI output back into the correct row using an update operation Along the way you’ll learn the three essential Google Sheets operations in n8n (read → append → update), see how to pass sheet data into an OpenAI node, and document each step with sticky-note instructions—perfect for anyone taking their first steps in no-code automation. 0 Prerequisites Google Sheets 1. Open Google Cloud Console → create / select a project. 2. Enable Google Sheets API under APIs & Services. 3. Create an OAuth Desktop credential and connect it in n8n. 4. Share the spreadsheet with the Google account linked to the credential. OpenAI 1. Create a secret key at <https://platform.openai.com/account/api-keys>. 2. In n8n → Credentials → New → choose OpenAI API and paste the key. Sample sheet to copy (make your own copy and use its link) <https://docs.google.com/spreadsheets/d/15i9WIYpqc5lNd5T4VyM0RRptFPdi9doCbEEDn8QglN4/edit?usp=sharing> --- 1 Trigger Manual Trigger – lets you run on demand while learning. (Swap for a Schedule or Webhook once you automate.) --- 2 Read existing rows Node: Get Rows from Google Sheets Reads every row from Sheet1 of your copied file. --- 3 Generate a demo row Node: Generate 1 Row of Data (Set node) Pretends a form was submitted: Name, Email, Topic, Submitted = "Yes" --- 4 Append the new row Node: Append Data to Google Operation append → writes to the first empty line. --- 5 Create a description with GPT-4o 1. OpenAI Chat Model – uses your OpenAI credential. 2. Write description (AI Agent) – prompt = the Topic. 3. Structured Output Parser – forces JSON like: { "description": "…" }. --- 6 Update that same row Node: Update Sheets data Operation update. Matches on column Email to update the correct line. Writes the new Description cell returned by GPT-4o. --- 7 Why this matters Demonstrates the three core Google Sheets operations: read → append → update. Shows how to enrich sheet data with an AI step and push the result right back. Sticky Notes provide inline docs so anyone opening the workflow understands the flow instantly. --- Need help? Robert Breen – Automation Consultant robert.j.breen@gmail.com <https://www.linkedin.com/in/robert-breen-29429625/>
by Robert BreenThis workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors competitor pricing changes and website updates to keep you informed of market movements. It saves you time by eliminating the need to manually check competitor websites and provides alerts only when actual changes occur, preventing information overload. Overview This workflow automatically scrapes competitor pricing pages (like ClickUp) and compares current pricing with previously stored data. It uses Bright Data to access competitor websites without being blocked and AI to intelligently extract pricing information, updating your tracking spreadsheet only when changes are detected. Tools Used n8n: The automation platform that orchestrates the workflow Bright Data: For scraping competitor websites without being blocked OpenAI: AI agent for intelligent pricing data extraction and parsing Google Sheets: For storing and comparing historical pricing data How to Install 1. Import the Workflow: Download the .json file and import it into your n8n instance 2. Configure Bright Data: Add your Bright Data credentials to the MCP Client node 3. Set Up OpenAI: Configure your OpenAI API credentials 4. Configure Google Sheets: Connect your Google Sheets account and set up your pricing tracking spreadsheet 5. Customize: Set your competitor URLs and pricing monitoring schedule Use Cases Product Teams: Monitor competitor feature and pricing changes for strategic planning Sales Teams: Stay informed of competitor pricing to adjust sales strategies Marketing Teams: Track competitor messaging and positioning changes Business Intelligence: Build comprehensive competitor analysis databases Connect with Me Website: https://www.nofluff.online YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get Bright Data: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #competitoranalysis #pricingmonitoring #brightdata #webscraping #competitortracking #marketintelligence #n8nworkflow #workflow #nocode #pricetracking #businessintelligence #competitiveanalysis #marketresearch #competitormonitoring #pricingdata #websitemonitoring #competitorpricing #marketanalysis #competitorwatch #pricingalerts #businessautomation #competitorinsights #markettrends #pricingchanges #competitorupdates #strategicanalysis #marketposition #competitiveintelligence
by Yaron BeenAutomate video ads with NanoBanana, Seedream 4, ChatGPT Image and Veo 3 Who is this for? This template is designed for marketers, content creators, and e-commerce brands who want to automate the creation of professional ad videos at scale. It’s ideal for teams looking to generate consistent, high-quality video ads for social media without spending hours on manual design, editing, or publishing. What problem is this workflow solving? / Use case Creating video ads usually requires multiple tools and a lot of time: writing scripts, designing product visuals, editing videos, and publishing them across platforms. This workflow automates the entire pipeline — from idea to ready-to-publish ad video — ensuring brands can quickly test campaigns and boost engagement without production delays. What this workflow does 1. Generates ad ideas from Telegram input (text + product image). 2. Creates product visuals using multiple AI image engines: Seedream 4.0 (realistic visuals) NanoBanana (image editing & enhancement) ChatGPT Image / GPT-4o (creative variations) 3. Produces cinematic video ads with Veo 3 based on AI-generated scripts. 4. Merges multiple short clips into a polished final ad. 5. Publishes automatically to multiple platforms (TikTok, Instagram, LinkedIn, X, Threads, Facebook, Pinterest, Bluesky, YouTube) via Blotato. 6. Stores metadata and results in Google Sheets & Google Drive for easy tracking. 7. Notifies you via Telegram with the video link and copy. Setup 1. Connect your accounts in n8n: Telegram API (for input and notifications) Google Drive + Google Sheets (storage & tracking) Kie AI API (Seedream + Veo 3) Fal.ai API (NanoBanana + video merging) OpenAI (for script and prompt generation) Blotato API (for social publishing) 2. Prepare a Google Sheet with brand info and settings (product name, category, features, offer, website URL). 3. Deploy the workflow and connect your Telegram bot to start sending ad ideas (photo + caption). 4. Run the workflow — it will automatically generate images, create videos, and publish to your chosen channels. How to customize this workflow to your needs Brand customization: Adjust the Google Sheet values to reflect your brand’s offers and product features. Platforms: Enable/disable specific Blotato nodes depending on which platforms you want to publish to. Video style: Edit the AI agent’s system prompt to control tone, format, and transitions (cinematic, playful, modern, etc.). Notifications: Adapt Telegram nodes to send updates to different team members or channels. Storage: Change the Google Drive folder IDs to store generated videos and images in your preferred location. This workflow lets you go from idea → images → cinematic ad video → auto-published content in minutes, fully automated. --- Watch This Tutorial: Step by Step --- Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
by Dr. FirasThis automation template turns any long video into multiple viral-ready short clips and auto-schedules them to TikTok, Instagram Reels, and YouTube Shorts. It works with both vertical and horizontal inputs and respects the original input resolution (no unnecessary upscaling), cropping or letterboxing intelligently when needed. The workflow automatically extracts between 3 and 6 clips (based on video length and the most engaging segments) and schedules one short per consecutive day—e.g., 3 clips → the next 3 days, 6 clips → the next 6 days. Note: This workflow uses OpenAI Whisper for word-level transcription, Google’s Gemini for clip selection and metadata, and Upload-Post’s FFmpeg API for GPU-accelerated cutting/cropping and social scheduling. You can use the same Upload-Post API token for both FFmpeg jobs and publishing uploads. Upload-Post also offers a generous free trial with no credit card required. Who Is This For? Creators & Editors: Batch-convert long talks/podcasts into daily Shorts/Reels/TikToks. Agencies & Social Teams: Turn webinars/interviews into a reliable short-form stream. Brands & Founders: Maintain a steady posting cadence with minimal hands-on editing. What Problem Does This Workflow Solve? Manual clipping is slow and inconsistent. This workflow: Finds Hooks Automatically: AI picks 3–6 high-retention segments from transcript + timestamps (count scales with video length/quality). Cuts Cleanly: Absolute-second FFmpeg timing to avoid mid-word cuts. Vertical & Horizontal Friendly: Handles both orientations and respects source resolution. Schedules for You: Posts one clip per day on consecutive days. How It Works 1. Form Upload: Submit your long video. 2. Audio Extraction: FFmpeg job extracts audio for accurate ASR. 3. Whisper Transcription: Word-level timestamps enable precise clipping. 4. AI Clip Mining (Gemini): Detects 3–6 “viral” moments (15–60s) and generates titles/descriptions. 5. Cut & Crop (FFmpeg): GPU pipeline produces clean clips; preserves input resolution/orientation when possible and crops/pads appropriately for target platforms. 6. Status & Download: Polls job status and retrieves the final clips. 7. Auto-Scheduling (Consecutive Days): Schedules one short per day starting tomorrow, for as many days as clips were produced (e.g., 3 clips → 3 days, 6 clips → 6 days) at a configurable time (default 20:00 Europe/Madrid). Setup 1. OpenAI (Whisper): Add your OpenAI API credentials. 2. Google Gemini: Add Gemini credentials used by the AI Agent node. 3. Upload-Post (free trial no credit card required): Generate your api token https://app.upload-post.com/ connect your social media accounts and add your API token credentials in n8n (same token works for FFmpeg jobs and publishing). 4. Scheduling: Adjust posting time/intervals and timezone (Europe/Madrid by default). 5. Metadata Mapping: Titles/descriptions are auto-generated per platform; tweak as needed. Requirements Accounts: n8n, OpenAI, Google (Gemini), Upload-Post, and social platform connections. API Keys: OpenAI token, Gemini credentials, Upload-Post token. Budget: Whisper + Gemini inference + FFmpeg compute + optional posting costs. Features Word-Accurate Cuts: Absolute-second timecodes with subtle pre/post-roll. Orientation-Aware: Supports vertical and horizontal inputs; preserves source resolution where possible. Platform-Optimized Output: 9:16-ready delivery with smart crop/pad behavior. Consecutive-Day Scheduler: 3–6 clips → 3–6 consecutive posting days, automatically. Retry & Polling: Built-in waits and status checks for robust processing. Modular: Swap models, adjust clip count/length, or add/remove platforms quickly. Turn long-form video into a consistent sequence of Shorts/Reels/TikToks—automatically, day after day, while respecting your source resolution.
by Juan Carlos Cavero GraciaCreate viral Ads with NanoBanana & Seedance, publish on socials via upload-post Who is this for? This workflow is designed for marketers, content creators, and small businesses who want to automate the creation of engaging social media ads without spending hours on manual design, video editing, or publishing. --- What problem is this workflow solving? / Use case Manually creating ads for multiple platforms is time-consuming and repetitive. You need to generate visuals, edit videos, add music, and then publish them across social channels. This workflow automates the end-to-end ad production pipeline, saving time while ensuring consistent, professional-quality output. --- What this workflow does Receives ad ideas via Telegram. Uses NanoBanana to generate and edit realistic product images. Transforms images into engaging short videos with Seedance. Generates background music with Suno. Merges video and audio into a polished final ad. Reads brand info and generates ad copy with AI (OpenAI). Publishes ads to Instagram, TikTok, YouTube, Facebook, and X via upload-post. Stores media and campaign data in Google Drive and Google Sheets for tracking. Sends back notifications and previews via Telegram. --- Setup 1. Connect your accounts: Telegram Google Drive Google Sheets OpenAI API NanoBanana API Seedance API Suno API Upload-post 2. Prepare Google Sheets: Add a sheet for brand details (name, category, features, website). Add another sheet for video logs (status, links, captions). 3. Configure upload-post: Ensure your social accounts (TikTok, Instagram, YouTube, Facebook, X) are linked to upload-post. --- How to customize this workflow to your needs Prompts → Adjust the image/video/music prompts to better reflect your brand’s tone and products. Ad copy → Modify the AI prompt inside the Ads Copywriter Generator to control wording, style, and structure. Publishing scope → Choose only the platforms you want (TikTok, Instagram, etc.) inside the upload-post node. Storage → Update Google Drive folder IDs and Google Sheets document IDs to match your own workspace. --- With this template, you get a fully automated viral ad production system powered by AI visuals, video rendering, and auto-publishing across social platforms. Perfect for scaling your content strategy while saving time. Documentation: Notion Guide Demo Video Watch the full tutorial here: YouTube Demo Need help customizing? Contact me for consulting and support : Linkedin / Youtube
by Dr. FirasYoutube Explanation: https://youtu.be/KgmNiV7SwkU This n8n workflow is designed to automate the initial intake and scheduling for a law firm. It's split into two main parts: 1. New Inquiry Handling: Kicks off when a potential client fills out a JotForm, saves their data, and sends them an initial welcome message on WhatsApp. 2. Appointment Scheduling: Activates when the client replies on WhatsApp, allowing an AI agent to chat with them to schedule a consultation. Here’s a detailed breakdown of the prerequisites and each node. ** Prerequisites Before building this workflow, you'll need accounts and some setup for each of the following services: JotForm JotForm Account: You need an active JotForm account. A Published Form: Create a form with the exact fields used in the workflow: Full Name, Email Address, Phone Number, I am a..., Legal Service of Interest, Brief Message, and How Did You Hear About Us?. API Credentials: Generate API keys from your JotForm account settings to connect it with n8n. Google Google Account: To use Google Sheets and Google Calendar. Google Sheet: Create a new sheet named "Law Client Enquiries". The first row must have these exact headers: Full Name, Email Address, Phone Number, client type, Legal Service of Interest, Brief Message, How Did You Hear About Us?. Google Calendar: An active calendar to manage appointments. Google Cloud Project: Service Account Credentials (for Sheets): In the Google Cloud Console, create a service account, generate JSON key credentials, and enable the Google Sheets API. You must then share your Google Sheet with the service account's email address (e.g., automation-bot@your-project.iam.gserviceaccount.com). OAuth Credentials (for Calendar): Create OAuth 2.0 Client ID credentials to allow n8n to access your calendar on your behalf. You'll need to enable the Google Calendar API. Gemini API Key: Enable the Vertex AI API in your Google Cloud project and generate an API key to use the Google Gemini models. WhatsApp Meta Business Account: Required to use the WhatsApp Business Platform. WhatsApp Business Platform Account: You need to set up a business account and connect a phone number to it. This is different from the regular WhatsApp or WhatsApp Business app. API Credentials: Get the necessary access tokens and IDs from your Meta for Developers dashboard to connect your business number to n8n. PostgreSQL Database A running PostgreSQL instance: This can be hosted anywhere (e.g., AWS, DigitalOcean, Supabase). The AI agent needs it to store and retrieve conversation history. Database Credentials: You'll need the host, port, user, password, and database name to connect n8n to it. Node-by-Node Explanation The workflow is divided into two distinct logical flows. Flow 1: New Client Intake from JotForm This part triggers when a new client submits your form. 1. JotForm Trigger What it does: This is the starting point. It automatically runs the workflow whenever a new submission is received for the specified JotForm (Form ID: 252801824783057). Prerequisites: A JotForm account and a created form. 2. Append or update row in sheet (Google Sheets) What it does: It takes the data from the JotForm submission and adds it to your "Law Client Enquiries" Google Sheet. How it works: It uses the appendOrUpdate operation. It tries to find a row where the "Email Address" column matches the email from the form. If it finds a match, it updates that row; otherwise, it appends a new row at the bottom. Prerequisites: A Google Sheet with the correct headers, shared with your service account. 3. AI Agent What it does: This node crafts the initial welcome message to be sent to the client. How it works: It uses a detailed prompt that defines a persona ("Alex," a legal intake assistant) and instructs the AI to generate a professional WhatsApp message. It dynamically inserts the client's name and service of interest from the Google Sheet data into the prompt. Connected Node: It's powered by the Google Gemini Chat Model. 4. Send message (WhatsApp) What it does: It sends the message generated by the AI Agent to the client. How it works: It takes the client's phone number from the data (Phone Number column) and the AI-generated text (output from the AI Agent node) to send the message via the WhatsApp Business API. Prerequisites: A configured WhatsApp Business Platform account. --- Flow 2: AI-Powered Scheduling via WhatsApp This part triggers when the client replies to the initial message. 1. WhatsApp Trigger What it does: This node listens for incoming messages on your business's WhatsApp number. When a client replies, it starts this part of the workflow. Prerequisites: A configured WhatsApp Business Platform account. 2. If node What it does: It acts as a simple filter. It checks if the incoming message text is empty. If it is (e.g., a status update), the workflow stops. If it contains text, it proceeds to the AI agent. 3. AI Agent1 What it does: This is the main conversational brain for scheduling. It handles the back-and-forth chat with the client. How it works: Its prompt is highly detailed, instructing it to act as "Alex" and follow a strict procedure for scheduling. It has access to several "tools" to perform actions. Connected Nodes: Google Gemini Chat Model1: The language model that does the thinking. Postgres Chat Memory: Remembers the conversation history with a specific user (keyed by their WhatsApp ID), so the user doesn't have to repeat themselves. Tools: Know about the user enquiry, GET MANY EVENTS..., and Create an event. 4. AI Agent Tools (What the AI can do) Know about the user enquiry (Google Sheets Tool): When the AI needs to know who it's talking to, it uses this tool. It takes the user's phone number and looks up their original enquiry details in the "Law Client Enquiries" sheet. GET MANY EVENTS... (Google Calendar Tool): When a client suggests a date, the AI uses this tool to check your Google Calendar for any existing events on that day to see if you're free. Create an event (Google Calendar Tool): Once a time is agreed upon, the AI uses this tool to create the event in your Google Calendar, adding the client as an attendee. 5. Send message1 (WhatsApp) What it does: Sends the AI's response back to the client. This could be a confirmation that the meeting is booked, a question asking for their email, or a suggestion for a different time if the requested slot is busy. How it works: It sends the output text from AI Agent1 to the client's WhatsApp ID, continuing the conversation.
by iamvaarAutomate LinkedIn content creation by managing ideas in Google Sheets, generating professional AI-written posts, intelligently selecting relevant Unsplash images, sending drafts for email approval, and publishing directly to LinkedIn. How it works Step 1: Scheduled Sheet Check Workflow runs daily at midnight (customizable to hourly/weekly) Fetches posts from Google Sheet marked with Status = "Ready" Processes one post per run, updates status to "In Progress" Step 2: AI Content Generation GPT-5.1 creates engaging LinkedIn post based on your inputs Generates content with proper hashtags, formatting, and tone Follows your specified content type (tip, story, announcement, etc.) Step 3: Quality Validation Automatically checks character limits (3000 max) Validates minimum hashtag requirements (3+) Loops back to regenerate if quality checks fail Step 4: Email Approval Workflow Formats post as HTML email with professional styling Sends preview to your Gmail for review Waits for your approval response before proceeding Nothing posts without explicit confirmation Step 5: Smart Image Handling If you provided image URL: Downloads from Google Drive, Dropbox, or direct links If no URL is provided: Fetch 10 images from Unsplash and use AI to select the best one. If "Include Image?" is "No": Posts text-only content Automatically converts share links to downloadable formats Step 6: LinkedIn Publishing & Tracking Posts approved content directly to your LinkedIn profile Uses appropriate API endpoint based on whether image is included Updates Google Sheet status to "Posted" for successful posts Marks "Rejected" posts in sheet for review and editing What you'll get Batch content planning: Queue multiple posts in advance via Google Sheets Consistent posting schedule: Automated daily publishing without manual work Professional AI content: GPT-5.1 generates engaging, platform-optimized posts Full approval control: Review every post before it goes live Flexible image options: Your images, AI-generated, or text-only Quality assurance: Built-in checks prevent poorly formatted posts Status tracking: Monitor what's ready, in progress, rejected, or posted Smart link conversion: Automatically handles Google Drive and Dropbox share links Requirements Accounts & credentials: OpenAI API key (requires paid plan for GPT-5.1) Gmail account (for approval workflow) Google account (for Sheets integration) LinkedIn account (for publishing) Unsplash API key (for getting images) Google Sheet setup: Create a sheet with these columns: Topic/Subject (required) - Main idea for the post Content Type (required) - e.g., "Tip", "Story", "Announcement" Tone (required) - e.g., "Professional", "Casual", "Inspirational" Target Audience (optional) - Who you're writing for Additional Notes (optional) - Specific points to include Image link for your post (optional) - URL to your image Include Image? (required) - "Yes" or "No" Status (required) - "Ready" to trigger workflow Setup steps 1. Import workflow - Click "Use workflow" to add to your n8n instance 2. Connect credentials: Google Sheets: Authenticate and select your sheet from dropdown OpenAI: Add your API key in both AI nodes Gmail: Authenticate and update recipient email in approval node LinkedIn: Authenticate (your profile auto-populates) 3. Create your content sheet - Add the required columns and fill with post ideas 4. Test the workflow: Add one test row with Status = "Ready" Run workflow manually Check email for approval Verify post appears on LinkedIn 5. Configure schedule - Default is daily at midnight; adjust Schedule Trigger node for different frequency 6. Start batching - Add multiple ideas to your sheet and let automation handle the rest Tips for best results Be specific in Topic/Subject: "5 ways to improve team productivity" beats "productivity tips" Mix content types and tones to keep your feed engaging Use Additional Notes for data points, statistics, or specific examples. You can also include links that the AI can use for the posts. Start with text-only posts to validate content quality before adding images Review rejected posts carefully and refine your inputs Batch 10-20 ideas at once for weeks of automated content
by Sona LabsGenerate product images with NanoBanana Pro to Veo videos and Blotato Who is this for? This workflow is designed for: Content creators and marketers E-commerce and product-based businesses Agencies producing social media visuals and videos Automation builders looking for AI-powered creative pipelines It is ideal for anyone who wants to automate product image and video creation using AI and publish content without manual work. --- What problem is this workflow solving? / Use case Creating product visuals and marketing videos usually requires multiple tools, manual prompt writing, and repetitive steps. This workflow solves: Manual image and video creation Inconsistent visual quality across assets Time-consuming prompt iteration Manual video publishing to social platforms The workflow automates the entire process from image generation to video publishing using AI. --- What this workflow does This workflow provides an end-to-end automation pipeline: 1. Generates high-quality product images using NanoBanana Pro 2. Applies Contact Sheet Prompting to explore multiple visual variations 3. Converts selected images into short marketing videos using Veo 3.1 4. Automatically publishes the final videos via BLOTATO The result is a fully automated creative workflow that turns AI prompts into ready-to-publish video content. --- Setup To use this workflow, you need the following services and credentials: OpenAI API Used for image analysis and prompt generation NanoBanana Pro (fal.ai) Product image generation API: https://fal.ai/models/fal-ai/nano-banana-pro/edit/api Veo 3.1 (fal.ai) Video generation API: https://fal.ai/models/fal-ai/veo3.1/first-last-frame-to-video Blotato Video publishing to social platforms Sign up at BLOTATO All credentials must be added in n8n before running the workflow. --- How to customize this workflow to your needs You can easily adapt this workflow by: Modifying AI prompts to match your brand style Adjusting image composition and realism parameters in NanoBanana Pro Changing video motion, pacing, and aspect ratio in Veo 3.1 Selecting different social platforms or publishing rules in Blotato Replacing or extending individual steps while keeping the same architecture The workflow is modular and can be reused for multiple products or campaigns. Watch This Tutorial --- Need help or want to customize this? Contact: LinkedIn YouTube: @DRFIRASS Workshops: Mes Ateliers n8n --- Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube / Mes Ateliers n8n
by Dr. FirasWho’s it for This template is built for WooCommerce store owners, eCommerce managers, and automation agencies who want to manage store operations directly from Telegram using an AI assistant. It’s ideal for users looking to save time, automate support, and access store data conversationally. How it works When a user sends a message via Telegram, the workflow triggers an AI agent that understands the request using a chat model with memory. Based on the intent, the agent executes the appropriate action such as retrieving orders, fetching product data, updating product information, logging data into Google Sheets, or sending email notifications. How to set up 1. Connect your Telegram bot credentials 2. Add your WooCommerce API keys 3. Connect Google Sheets for data storage 4. Connect your Gmail account 5. Configure your OpenRouter or OpenAI API key 6. Test the workflow via Telegram commands Requirements WooCommerce store with API access Telegram bot token Google Sheets account Gmail credentials OpenRouter or OpenAI API key How to customize You can expand this agent by adding tools like order creation, refund processing, CRM integrations, shipping updates, or advanced reporting. The AI prompt can also be modified to match your store operations.
by Nid AcademyAI-Enriched Cold Outreach: Research → Draft → QA → Write-back ============================================================ What this template does ----------------------- Automates cold email drafting from a lead list by: 1. Enriching each lead with LinkedIn profile, LinkedIn company, and Crunchbase data 2. Generating a personalized subject + body with Gemini 3. Auto-reviewing with a Judge agent and writing back only APPROVED drafts to your Data Table Highlights ----------- Hands-off enrichment via RapidAPI; raw JSON stored back on each row Two-agent pattern: Creative Outreach Agent (draft) + Outreach Email Judge (QA) Structured outputs guaranteed by LangChain Structured Output Parsers Data Table–native: reads “unprocessed” rows, writes results to the same row Async polling with Wait nodes for scraper task results How it works (flow) ------------------- 1. Trigger: Manual (replace with Cron if needed) 2. Fetch leads: Data Table “Get row(s)” filters rows where email_subject is empty (pending) 3. Loop: Split in Batches iterates rows 4. Enrichment (runs in parallel): LinkedIn profile: HTTP (company_url) → Wait → Results → Data Table update → linkedin_profile_scrape LinkedIn company: HTTP (company_url) → Wait → Results → Data Table update → linkedin_company_scrape Crunchbase company: HTTP (url_search) → Wait → Results → Data Table update → crunchbase_company_scrape (All calls use host cold-outreach-enrichment-scraper with a RapidAPI key.) 5. Draft (Gemini): “Agent One” composes a concise, personalized email using row fields + enrichment + ABOUT ME block. Structured Output Parser enforces: ``json { "email_subject": "text", "email_content": "text" } ` 6. Prep for QA: “Email Context” maps email_subject, email_content, and email for the judge. 7. QA (Judge): “Judge Agent” returns APPROVED or REVISE (brief feedback allowed). 8. Route: If APPROVED → Data Table “Update row(s)” writes email_subject + email_body (a.k.a. email_content) back to the row. If REVISE → Skipped; loop continues. Required setup --------------- Data Table: “email_linkedin_list” (or your own) with at least: email, First_name, Last_name, Title, Location, Company_Name, Company_site, Linkedin_URL, company_linkedin (if used), Crunchbase_URL, email_subject, email_body, linkedin_profile_scrape, linkedin_company_scrape, crunchbase_company_scrape (string fields for JSON). Credentials: RapidAPI key for cold-outreach-enrichment-scraper (store securely as credential, not hardcoded) Google Gemini (PaLM) API configured in the Google Gemini Chat Model node ABOUT ME block: Replace the sample persona (James / CEO / Company Sample / AI Automations) with your own. Nodes used ----------- Data Table HTTP Request: AI Agent: Google Gemini Chat Model Split in Batches: Main Loop Set: RapidAPI-Key Customization ideas ------------------- Process flags: Add email_generated_at or processed` boolean to prevent reprocessing. Human-in-the-loop: Send drafts to Slack/Email for spot check before write-back. Delivery: After approval, optionally email the draft to the sender for review. Quotas & costs --------------- RapidAPI: Multiple calls per row (three tasks + result polls). Gemini: Token usage for generator + judge per row. Tune batch size and schedule accordingly. Privacy & compliance -------------------- You are scraping and storing person/company data. Ensure lawful basis, respect ToS, and minimize stored data.
by Johnny RafaelUse the n8n Data Tables feature to store, retrieve, and analyze survey results — then let OpenAI automatically recommend the most relevant course for each respondent. --- What this workflow does This workflow demonstrates how to use n8n’s built-in Data Tables to create an internal recommendation system powered by AI. It: Collects survey responses through a Form Trigger Saves responses to a Data Table called Survey Responses Fetches a list of available courses from another Data Table called Courses Passes both Data Tables into an OpenAI Chat Agent, which selects the most relevant course Returns a structured recommendation with: course: the course title reasoning: why it was selected > Trigger: Form submission (manual or public link) --- Who it’s for Perfect for educators, training managers, or anyone wanting to use n8n Data Tables as a lightweight internal database — ideal for AI-driven recommendations, onboarding workflows, or content personalization. --- How to set it up 1 Create your n8n Data Tables This workflow uses two Data Tables — both created directly inside n8n. Table 1: Survey Responses Columns: Name Q1 — Where did you learn about n8n? Q2 — What is your experience with n8n? Q3 — What kind of automations do you need help with? To create: 1. Add a Data Table node to your workflow. 2. From the list, click “Create New Data Table.” 3. Name it Survey Responses and add the columns above. --- Table 2: Courses Columns: Course Description To create: 1. Add another Data Table node. 2. Click “Create New Data Table.” 3. Name it Courses and create the columns above. 4. Copy course data from this Google Sheet: https://docs.google.com/spreadsheets/d/1Y0Q0CnqN0w47c5nCpbA1O3sn0mQaKXPhql2Bc1UeiFY/edit?usp=sharing This Courses Data Table is where you’ll store all available learning paths or programs for the AI to compare against survey inputs. --- 2 Connect OpenAI 1. Go to OpenAI Platform 2. Create an API key 3. In n8n, open Credentials → OpenAI API and paste your key 4. The workflow uses the gpt-4.1-mini model via the LangChain integration --- Key Nodes Used | Node | Purpose | n8n Feature | |------|----------|-------------| | Form Trigger | Collect survey responses | Forms | | Data Table (Upsert) | Stores results in Survey Responses | Data Tables | | Data Table (Get) | Retrieves Courses | Data Tables | | Aggregate + Set | Combines and formats table data | Core nodes | | OpenAI Chat Model (LangChain Agent) | Analyzes responses and courses | AI | | Structured Output Parser | Returns structured JSON output | LangChain | --- Tips for customization Add more Data Table columns (e.g., email, department, experience years) Use another Data Table to store AI recommendations or performance results Modify the Agent system message to customize how AI chooses courses Send recommendations via Email, Slack, or Google Sheets --- Why Data Tables? This workflow shows how n8n’s Data Tables can act as your internal database: Create and manage tables directly inside n8n No external integrations needed Store structured data for AI prompts Share tables across multiple workflows All user data and course content are stored securely and natively in n8n Cloud or Self-Hosted environments. --- Contact Need help customizing this (e.g., expanding Data Tables, connecting multiple surveys, or automating follow-ups)? robert@ynteractive.com Robert Breen ynteractive.com
by Robert BreenTurn any prompt into structured web data. Send a POST request with a natural language prompt and an optional JSON schema, and get back clean, structured results scraped from the web by an AI agent powered by Firecrawl. Use Cases Data Enrichment: Feed company names or URLs from your CRM and get back structured firmographic data (industry, funding, team size, tech stack). Lead Generation: Ask the agent to find pricing, contact pages, or product details for a list of competitors. Market Research: Extract structured pricing plans, feature comparisons, or product catalogs from any website. Content Aggregation: Pull structured news, events, or job postings from across the web on a schedule. Sales Intelligence: Enrich prospect lists with company info, recent news, or tech stack details before outreach. How It Works `` POST /webhook/scrape-agent ` 1. Receive Scrape Request receives a POST request with prompt and an optional output_schema. 2. Validate Output Schema checks the schema. If none is provided, it falls back to a permissive default. If the schema is malformed, it returns a clear error via Return Schema Error. 3. Research & Extract Web Data takes the prompt and uses the full Firecrawl toolkit to research the web: Search (/search): Finds relevant pages and sources across the web. Scrape (/scrape): Extracts clean, structured content from any URL. Interact (interactContext, interact, interactStop): Lets the agent interact with scraped pages in a live session. After scraping a page, the agent can click buttons, fill forms, navigate dynamic content, and extract data that static scraping cannot reach, all without managing sessions manually. This combination gives the AI agent complete web navigation capabilities. It can discover sources, read pages, and interact with dynamic content autonomously. 4. Format Response to Schema (Structured Output Parser) formats the agent's response to match the provided (or default) schema. 5. Return Structured Results sends the structured JSON back to the caller. Setup Requirements Firecrawl API Key: Sign up at firecrawl.dev and grab your API key. Connect it in the Firecrawl credential nodes. LLM Provider: Configure your Primary Chat Model and Fallback Chat Model nodes (e.g., OpenRouter, OpenAI, Anthropic). The template uses two model nodes for reliability, plus a separate Parser Chat Model for the output parser. n8n Instance: Self-hosted or cloud. Make sure the webhook node is set to accept POST requests. API Reference Endpoint ` POST https://your-n8n-instance/webhook/scrape-agent ` Request Body | Field | Type | Required | Description | |-------|------|----------|-------------| | prompt | string | Yes | Natural language instruction for the agent | | output_schema | object | No | JSON Schema defining the desired output structure | Response Returns a JSON object matching the provided schema, or a flexible object if no schema was given. --- Testing Examples 1. Basic Request (No Schema) The agent decides the output structure on its own. `bash curl -X POST "https://your-n8n-instance/webhook/scrape-agent" \ -H "Content-Type: application/json" \ -d '{ "prompt": "Find the latest pricing for Firecrawl" }' | jq ` Expected output: A JSON object with whatever structure the agent finds most appropriate for the data. Since no schema was provided, the internal default ({ "type": "object", "additionalProperties": true }) is used. 2. Request With a Custom Schema You define exactly the shape of data you want back. `bash curl -X POST "https://your-n8n-instance/webhook/scrape-agent" \ -H "Content-Type: application/json" \ -d '{ "prompt": "Find the latest pricing for Firecrawl", "output_schema": { "type": "object", "properties": { "source": { "type": "string" }, "plans": { "type": "array", "items": { "type": "object", "properties": { "name": { "type": "string" }, "price": { "type": "string" }, "credits": { "type": "string" }, "highlights": { "type": "array", "items": { "type": "string" } } } } } } } }' | jq ` Expected output: `json { "output": { "source": "https://www.firecrawl.dev/pricing", "plans": [ { "name": "Free", "price": "$0 (one-time)", "credits": "500 credits (one-time)", "highlights": [ "Scrape up to 500 pages", "2 concurrent requests", "Low rate limits", "No credit card required" ] }, { "name": "Hobby", "price": "$16/month (billed yearly, save $38)", "credits": "3,000 credits / month", "highlights": [ "Scrape up to 3,000 pages", "5 concurrent requests", "Basic support", "$9 per extra 1k credits" ] } ] } } ` 3. Invalid Schema (String Instead of Object) `bash curl -X POST "https://your-n8n-instance/webhook/scrape-agent" \ -H "Content-Type: application/json" \ -d '{ "prompt": "Find the latest pricing for Firecrawl", "output_schema": "not a valid schema" }' | jq ` Expected output: `json { "error": true, "message": "Invalid output_schema: must be a JSON object with a valid 'type' property (object, array, string, number, boolean)", "example_schema": { "type": "object", "properties": { "name": { "type": "string" }, "price": { "type": "number" } } } } ` 4. Invalid Schema (Array Instead of Object) `bash curl -X POST "https://your-n8n-instance/webhook/scrape-agent" \ -H "Content-Type: application/json" \ -d '{ "prompt": "Find the latest pricing for Firecrawl", "output_schema": [1, 2, 3] }' | jq ` Expected output: Same error response as above. 5. Invalid Schema (Missing type Property) `bash curl -X POST "https://your-n8n-instance/webhook/scrape-agent" \ -H "Content-Type: application/json" \ -d '{ "prompt": "Find the latest pricing for Firecrawl", "output_schema": { "properties": { "name": { "type": "string" } } } }' | jq ` Expected output: Same error response as above. 6. Invalid Schema (Invalid type Value) `bash curl -X POST "https://your-n8n-instance/webhook/scrape-agent" \ -H "Content-Type: application/json" \ -d '{ "prompt": "Find the latest pricing for Firecrawl", "output_schema": { "type": "banana" } }' | jq ` Expected output: Same error response as above. --- Workflow Architecture ` Receive Scrape Request (POST) | v Validate Output Schema |--- Error --> Return Schema Error (error JSON) |--- Success --> Research & Extract Web Data (AI Agent) | |--- Primary Chat Model |--- Fallback Chat Model |--- Search & Scrape: | - /search with Firecrawl | - /scrape with Firecrawl |--- Interact Tool: | - Interact context with Firecrawl | - Execute interaction with Firecrawl | - Stop interaction with Firecrawl | v Return Structured Results | |--- Format Response to Schema (Output Parser) | |--- Parser Chat Model ` Schema Validation Logic The Validate Output Schema node runs this validation before passing data to the agent: If output_schema is missing or null, the default permissive schema is used: { "type": "object", "additionalProperties": true }. If output_schema is present, it must be a JSON object (not a string, array, or primitive). It must have a type property with a valid value: object, array, string, number, or boolean. If validation fails, the workflow returns an error response with a helpful message and example schema. Notes The Format Response to Schema node (Structured Output Parser) requires the schema to be passed as a JSON string. The expression {{ JSON.stringify($('Validate Output Schema').item.json.output_schema) }}` handles this conversion. The agent has access to Firecrawl's full toolkit: search, scrape, and interact. With all three connected, the agent has complete web navigation powers. It can discover sources via search, extract content via scrape, and interact with dynamic JavaScript-heavy pages via interact. The interact tools let the agent scrape a page first and then continue working with it in a live session, clicking buttons, filling forms, and navigating deeper, all without manual session management. The agent autonomously decides which tools to use based on the prompt. Response times vary depending on the complexity of the prompt and how many pages the agent needs to visit. Simple lookups take a few seconds; deep research can take longer.
by FirecrawlWho it's for This workflow is for professionals and small business owners who receive a high volume of emails and want to automate triage, labeling, and draft reply generation — without losing the human touch before sending. How it works 1. A Gmail trigger polls the inbox every minute for new unread emails and retrieves the current date. 2. The full email message is fetched, and any existing processing labels are stripped from the thread. 3. A Gemini 2.5 Pro AI Agent reads the email (and the full thread via a Gmail Thread tool), checks Google Calendar for availability, then classifies the email into one of six categories (Urgent, Reply, Read, Notification, Newsletter, Invoice) and drafts an HTML reply when needed. 4. A Switch node routes the output: emails requiring a reply (Urgent or Reply) pass through a JavaScript node that appends an HTML signature before saving the message as a Gmail draft. 5. All paths converge to fetch the matching Gmail label, filter for validity, apply it to the thread, and mark the message as unread so it surfaces for human review. How to set up [ ] Connect a Gmail OAuth2 credential to all Gmail nodes (trigger, fetch, remove label, draft, label, mark unread) [ ] Connect a Google Gemini (PaLM) API credential to the Gemini Chat Model node [ ] Connect a Google Calendar OAuth2 credential to the Google Calendar Tool node [ ] Configure the Gmail Trigger label/filter to match your inbox setup [ ] Update the label IDs in Remove Label from Thread, Get label for response, and Labelliser to match your Gmail labels [ ] Customize the HTML signature in the Build HTML Signature code node Requirements Gmail account with OAuth2 access Google Gemini (PaLM) API key Google Calendar account How to customize Adjust the AI Agent's system prompt to change tone, add new label categories, or modify the reply structure. Extend the Switch node with additional branches (e.g., forward to a team member, archive automatically, create a CRM task). Replace the Gmail draft step with a direct send for fully automated responses on low-risk categories like Notifications.
by Allan VaccariziThis n8n template automates the collection, storage, and summarization of technology news and discussions from the n8n Community and Reddit (r/n8n). If you like staying informed but want to reduce daily manual browsing distractions, this workflow is perfect for you. How it works User Intent Detection: The workflow receives your Telegram message and uses an AI Agent (powered by Gemini/Groq) to intelligently classify your intent (Search, Deep-dive, or Casual Chat). Multi-Platform Scraping: Automatically fetches the latest discussions, topics, and comments from the official n8n Community and Reddit via HTTP Requests. Smart Summarization: Extracts complex HTML content and uses the AI to provide concise overviews, or deep-dives into specific forum threads with full contextual history. Seamless Delivery: Formats the AI's response into clean, chunked Telegram messages (handling limits smoothly) and delivers it straight to your chat. Daily Pulse: A scheduled trigger automatically aggregates the hottest topics every morning to keep you updated. How to use 1. Connect your Telegram Bot account to n8n. 2. Connect your Google Gemini and Groq API credentials. 3. (Optional) Connect your MongoDB instance if you want to enable long-term persistent chat memory. 4. Update the Chat ID in the Telegram nodes to route the scheduled Daily Pulse directly to your personal account or group. 5. Activate the workflow and start messaging your new AI assistant. Requirements n8n Version: Built and tested on n8n 2.9.4+. (Note: You may encounter errors on older versions. It is highly recommended to update to the latest n8n version to use this workflow effectively). Telegram Bot token. Google Gemini & Groq API keys. (Optional) MongoDB connection string. Customizing this workflow Change the AI Model: Swap the Gemini or Groq nodes for OpenAI, Claude, or any other supported LLM. Expand the Sources: Duplicate the HTTP Request nodes and adjust the HTML extractors to monitor other platforms like Discord or StackOverflow. Adjust the Schedule: Prefer chat over daily emails? Change the Cron expression to receive weekly summaries or disable it entirely to rely purely on on-demand Telegram queries. --- About the Author Created by: Nguyen Thieu Toan (Jay Nguyen) Email: me@nguyenthieutoan.com Website: nguyenthieutoan.com Company: CEO/Founder of GenStaff (genstaff.net) - AI Staffing Solutions Socials (Facebook / X / LinkedIn): @nguyenthieutoan More templates: n8n.io/creators/nguyenthieutoan
by Nguyễn Thiệu Toàn (Jay Nguyen)Run an AI-powered degree audit for each senior student. This template reads student rows from Google Sheets, evaluates completed courses against hard-coded program requirements, and writes back an AI Degree Summary of what's still missing (major core, Gen Eds, major electives, and upper-division credits). It's designed for quick advisor/registrar review and SIS prototypes. Trigger: Manual — When clicking "Execute workflow" Core nodes: Google Sheets, OpenAI Chat Model, (optional) Structured Output Parser Programs included: Computer Science BS, Business Administration BBA, Psychology BA, Mechanical Engineering BS, Biology BS (Pre-Med), English Literature BA, Data Science BS, Nursing BSN, Economics BA, Graphic Design BFA Who's it for Registrars & advisors who need fast, consistent degree checks Student success teams building prototype dashboards SIS/EdTech builders exploring AI-assisted auditing How it works 1. Read seniors from Google Sheets (Senior_data) with: StudentID, Name, Program, Year, CompletedCourses. 2. AI Agent compares CompletedCourses to built-in requirements (per program) and computes Missing items + a short Summary. 3. Write back to the same sheet using "Append or update" by StudentID (updates AI Degree Summary; you can also map the raw Missing array to a column if desired). Example JSON (for one student): { "StudentID": "S001", "Program": "Computer Science BS", "Missing": [ "GEN-REMAIN | General Education credits remaining | 6", "CS-EL-REM | CS Major Electives (200+ level) | 6", "UPPER-DIV | Additional Upper-Division (200+ level) credits needed | 18", "FREE-EL | Free Electives to reach 120 total credits | 54" ], "Summary": "All core CS courses are complete. Still need 6 Gen Ed credits, 6 CS electives, and 66 total credits overall, including 18 upper-division credits — prioritize 200/300-level CS electives." } Setup (2 steps) 1) Connect Google Sheets (OAuth2) In n8n → Credentials → New → Google Sheets (OAuth2) and sign in. In the Google Sheets nodes, select your spreadsheet and the Senior_data tab. Ensure your input sheet has at least: StudentID, Name, Program, Year, CompletedCourses. 2) Connect OpenAI (API Key) In n8n → Credentials → New → OpenAI API, paste your key. In the OpenAI Chat Model node, select that credential and a model (e.g., gpt-4o or gpt-5). Requirements Sheet columns: StudentID, Name, Program, Year, CompletedCourses CompletedCourses format: pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101). Program labels: should match the built-in list (e.g., Computer Science BS). Credits/levels: Template assumes upper-division ≥ 200-level (adjust the prompt if your policy differs). Customization Change requirements: Edit the Agent's system message to update totals, core lists, elective credit rules, or level thresholds. Store more output: Map Missing to a new column (e.g., AI Missing List) or write rows to a separate sheet for dashboards. Distribute results: Email summaries to advisors/students (Gmail/Outlook), or generate PDFs for advising folders. Add guardrails: Extend the prompt to enforce residency, capstone, minor/cognate constraints, or per-college Gen Ed variations. Best practices (per n8n guidelines) Sticky notes are mandatory: Include a yellow sticky note that contains this description and quick setup steps; add neutral sticky notes for per-step tips. Rename nodes clearly: e.g., "Get Seniors," "Degree Audit Agent," "Update Summary." No hardcoded secrets: Use credentials—not inline keys in HTTP or Code nodes. Sanitize identifiers: Don't ship personal spreadsheet IDs or private links in the published version. Use a Set node for config: Centralize user-tunable values (e.g., column names, tab names). Troubleshooting OpenAI 401/429: Verify API key/billing; slow concurrency if rate-limited. Empty summaries: Check column names and that CompletedCourses uses |. Program mismatch: Align Program labels to those in the prompt (exact naming recommended). Sheets auth errors: Reconnect Google Sheets OAuth2 and re-select spreadsheet/tab. Limitations Not an official audit: It infers gaps from the listed completions; registrar rules can be more nuanced. Catalog drift: Requirements are hard-coded in the prompt—update them each term/year. Upper-division heuristic: Adjust the level threshold if your institution defines it differently. Tags & category Category: Education / Student Information Systems Tags: degree-audit, registrar, google-sheets, openai, electives, upper-division, graduation-readiness Changelog v1.0.0 — Initial release: Senior_data in/out, 10 programs, AI Degree Summary output, append/update by StudentID. Contact Need help tailoring this to your catalog (e.g., per-college Gen Eds, capstones, minors, PDFs/email)? rbreen@ynteractive.com robert@ynteractive.com Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/ ynteractive.com — https://ynteractive.com
by Robert BreenDescription: Automate your entire supplier negotiation process with this AI-driven workflow that intelligently drafts, refines, and sends negotiation emails . Using advanced LLM reasoning and multi-angle strategies , it generates high-converting negotiation messages tailored to each supplier scenario. The workflow tracks replies, sends smart follow-ups , and logs outcomes automatically for full visibility. Perfect for procurement teams looking to reduce costs and eliminate manual back-and-forth communication . What This Template Does: Triggers when a new supplier entry is added to Google Sheets. Validates and structures supplier, product, and pricing data. Generates 3 AI-powered negotiation email drafts using different strategies. Selects the best-performing draft based on scoring logic. Refines the draft using AI self-critique for better tone and clarity. Sends the final negotiation email to the supplier via Gmail. Waits 24 hours and checks for supplier replies automatically. Detects whether a reply is received and routes the workflow accordingly. Sends an optimized follow-up email if no response is received. Logs negotiation details and outcomes in Notion. Updates Google Sheets with final status, pricing, and savings. Notifies the procurement team via Slack with results or retry alerts. Key Benefits: Fully autonomous negotiation process with zero manual effort AI-optimized messaging increases chances of better pricing Smart follow-ups ensure no supplier opportunity is missed Centralized tracking across Sheets, Notion, and Slack Data-driven decision making with scoring and insights Scalable procurement operations for high-volume supplier outreach Features: Google Sheets trigger-based workflow AI-powered negotiation using GPT-4o (multi-angle + self-critique) Automated email sending and reply detection via Gmail Intelligent retry logic using DPO-style optimization Notion logging for audit trails and reporting Slack alerts for real-time team notifications Built-in validation and structured data processing Requirements: Google Sheets account (for supplier data tracking) Gmail account (for sending and receiving emails) OpenAI API key (for AI-generated negotiation logic) Notion account (for logging negotiation outcomes) Slack account (for team notifications) Target Audience: Procurement and sourcing teams E-commerce and retail businesses managing suppliers Startups scaling vendor negotiations Automation agencies building AI-driven business workflows
by Rahul JoshiQuick Overview This workflow lets users manage Google Calendar by sending text or voice messages to a Zalo Official Account bot, transcribing voice notes with Google Gemini and using an OpenAI-powered agent to create, update, list, or delete events, then replying in Zalo with the result. How it works 1. Receives an incoming text or voice message through a Zalo Bot trigger. 2. Sends a typing indicator back to the Zalo chat and normalizes key message fields (chat ID, type, text, and voice URL). 3. If the message is a voice note, sends the audio URL to Google Gemini to transcribe it into text. 4. Sends the combined text/transcription to an OpenAI chat model agent that interprets the request in Vietnamese and decides whether to list, create, update, or delete a Google Calendar event. 5. Uses Google Calendar tools to get events and then create, update, or delete the targeted event based on the agent’s extracted parameters. 6. Sends the agent’s Markdown-formatted response back to the user in Zalo, and posts an error message to Zalo if the agent run fails. Setup 1. Install the community node package n8n-nodes-zalo-bot-official and restart n8n if required. 2. Connect your Zalo Bot API credentials and configure the Zalo webhook URL in your Zalo Official Account so incoming messages reach this workflow. 3. Add a Google Calendar OAuth2 credential and set the target calendar account (currently configured as toannguyen96vn@gmail.com) for all calendar operations. 4. Add a Google Gemini (PaLM) API credential for audio transcription and ensure voice messages include a reachable voice_url. 5. Add an OpenAI API credential, select the chat model you want to use (currently gpt-5-mini), and adjust the system prompt/tone if needed.
by Nguyễn Thiệu Toàn (Jay Nguyen)