Actioning your meeting next steps using transcripts and AI
This n8n workflow demonstrates how you can summarise and automate post-meeting actions from video transcripts fed into an AI Agent. Save time between meetings by allowing AI handle the chores of organising follow-up meetings and invites. How it works This workflow scans for the calendar for client or team meetings which were held online. Attempts will be made to fetch any recorded transcripts which are then sent to the AI agent. The AI agent summarises and identifies if any follow-on meetings are required. If found, the Agent will use its Calendar Tool to to create the event for the time, date and place for the next meeting as well as add known attendees. Requirements Google Calendar and the ability to fetch Meeting Transcripts (There is a special OAuth permission for this action!) OpenAI account for access to the LLM. Customising the workflow This example only books follow-on meetings but could be extended to generate reports or send emails.
By JimleukBuild custom workflows automatically with GPT-4o, RAG, and web search
🚀 What the “Agent Builder” template does Need to turn a one-line chat request into a fully-wired n8n workflow template—complete with AI agents, RAG, and web-search super-powers—without lifting a finger? That’s exactly what Agent Builder automates: Listens to any incoming chat message (via the Chat Trigger). Spins up an AI architect that analyses the request, searches the web, reads n8n docs from a Pinecone vector store, and designs the smallest possible set of nodes. Auto-generates a ready-to-import JSON template and hands it back as a downloadable file—plus all the supporting assets (embeddings, vector store etc.) so the next prompt is even smarter. Think of it as your personal “workflow chef”: you shout the order, it shops for ingredients, cooks, plates, and serves the meal. All you do is eat. --- 🤗 Who will love this? No-code builders / power users who don’t want to wrestle with AI node wiring. Agencies & consultants delivering lots of bespoke automations. Internal platform teams who need a “workflow self-service portal” for non-technical colleagues. --- 🧩 How it’s wired | Sub-process | What happens inside | Key nodes | | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------- | | Web Crawler (optional) | Firecrawl scrapes docs.n8n.io (or any URL you drop in) and streams raw markdown back. | Set URL → HTTP Request (Extract) → Wait & Retry | | RAG Trainer | Splits the scraped docs, embeds them with OpenAI, and upserts vectors into Pinecone. | Recursive Text Splitter → Embeddings OpenAI → Train Pinecone | | Agent Builder | The star of the show – orchestrates GPT-4o (via OpenRouter), SerpAPI web-search, your Pinecone index and a Structured Output Parser to produce → validate → prettify the final n8n template. | Chat Trigger → AI Agent → OpenAI (validator) → Code (extract) → Convert to JSON file | Every arrow in the drawn workflow is pre-connected, so the generated template always passes n8n’s import check. --- 🛠️ Getting set up (5 quick creds) | Service | Credential type | | --------------------------------------------------- | ---------------------------------------------------------- | | OpenAI / Azure OpenAI – embeddings & validation | OpenAI API | | Pinecone – vector store | Pinecone API | | OpenRouter – GPT-4o LLM | OpenRouter API Key | | SerpAPI – web search | SerpAPI Key | | Firecrawl (only if you plan to crawl) | Generic Header Auth → Authorization: Bearer YOUR_KEY | Each node already expects those creds; just create them once, select in the dropdown, hit Activate. --- 🏃♀️ What a typical run looks like User says: “Build me a workflow that monitors our support inbox, summarises new tickets with GPT and posts to Slack.” Chat Trigger captures the message. AI Agent: queries Pinecone for relevant n8n docs, fires a SerpAPI search for “n8n gmail trigger example”, sketches an architecture (Gmail Trigger → GPT Model → Slack). The agent returns JSON ➜ OpenAI node double-checks field names, connections, type versions. A tiny JS Code node slices the JSON out of the chat blob and saves it as template.json ready for download. You download, import, and… done. --- ✏️ Customising Switch the LLM – plug in Claude 3, Gemini 1.5, or a local model; just swap the OpenRouter Chat Model* node. Point the RAG at your own docs – change the crawl URL or feed PDFs via the Default Data Loader*. Hard-code preferred nodes – edit the “User node preferences” in the system message so the agent always chooses Notion* for databases, etc. --- 🥡 Take-away notes It's a prototype feel free to experiment with it to improve its capabilities. Have fun building!
By FranzScrape every URL on the web without getting blocked by Anti-Bot technologies with Scrappey
Purpose of the workflow Most scraping workflows get blocked by anti-bot technologies. To avoid this, you can use Scrappey to scrape every website you want. How it works: We use Test Data and make a API Call to the Scrappey service. We get the scraped website data back as a result. Setup Steps: Replace YOURAPIKEY in the "Scrappey API Call" node with your Scrappey API Key (Register For Free) Replace the test data with your production data. You can plug in any type of data connector at this point of your workflow.
By BelaAI blog generator for Shopify product listings: Using GPT-4o and Google Sheets
🧠 AI Blog Generator for Shopify Products using GPT-4o The AI Blog Generator is an advanced automation workflow powered by n8n, integrating GPT-4o and Google Sheets to generate SEO-rich blog articles for Shopify products. It automates the entire process — from pulling product data, analyzing images for nutritional information, to producing structured HTML content ready for publishing — with zero manual writing. --- 💡 Key Advantages 🔗 Shopify Product Sync Automatically pulls product data (title, description, images, etc.) via Shopify API. 🤖 AI-Powered Nutrition Extraction Uses GPT-4o to intelligently analyze product images and extract nutritional information. ✍️ SEO Blog Generation GPT-4o generates blog titles, meta descriptions, and complete articles using both product metadata and extracted nutritional info. 🗂️ Structured Content Output Produces well-formatted HTML with headers, bullet points, and nutrition tables for seamless Shopify blog integration. 📄 Google Sheets Integration Tracks blog creation, manages retries, and prevents duplicate publishing using a centralized Google Sheet. 📤 Shopify Blog API Integration Publishes the generated blog to Shopify using a two-step blog + article API call. --- ⚙️ How It Works Manual Trigger Initiate the process using a test trigger or a scheduler. Fetch Products from Shopify Retrieves all product details including descriptions and images. Extract Product Images Splits and processes each image individually. OCR + Nutrition AI GPT-4o reads nutrition facts from product images. Skips items without valid info. Check Existing Logs References a Google Sheet to avoid duplicates and determine retry status. AI Blog Generation Creates a blog with headings, bullet points, intro, and a nutrition table. Shopify Blog + Article Posting Uses the Shopify API to publish the blog and its content. Update Google Sheet Logs the blog URL, HTML content, errors, and status for future reference. --- 🛠️ Setup Steps Shopify Node: Connects to your Shopify store and fetches product data. Split Out Node: Divides product images for individual OCR processing. OpenAI Node: Uses GPT-4o to extract nutrition data from images. If Node: Filters for entries with valid nutrition information. Edit Fields Node: Formats the product data for AI processing. AI Agent Node: Generates SEO blog content. Google Sheets Nodes: Reads and updates blog creation status. HTTP Request Nodes: Posts the blog and article via Shopify’s API. --- 🔐 Credentials Required Shopify Access Token – For retrieving product data and posting blogs OpenAI API Key – For GPT-4o-based AI generation and image processing Google Sheets OAuth – For accessing the log sheet --- 👤 Ideal For Ecommerce teams looking to automate content for hundreds of products Shopify store owners aiming to boost organic traffic through blogging Marketing teams building scalable, AI-driven content workflows --- 💬 Bonus Tip The workflow is modular. You can easily extend it with internal linking, language translation, or even social media sharing — all within the same n8n flow.
By Kumar ShivamAnalyze cryptocurrency market data with HTX API, GPT-4o and Telegram
A fully autonomous, HTX Spot Market AI Agent (Huobi AI Agent) built using GPT-4o and Telegram. This workflow is the primary interface, orchestrating all internal reasoning, trading logic, and output formatting. --- ⚙️ Core Features 🧠 LLM-Powered Intelligence: Built on GPT-4o with advanced reasoning ⏱️ Multi-Timeframe Support: 15m, 1h, 4h, and 1d indicator logic 🧩 Self-Contained Multi-Agent Workflow: No external subflows required 🧮 Real-Time HTX Market Data: Live spot price, volume, 24h stats, and order book 📲 Telegram Bot Integration: Interact via chat or schedule 🔄 Autonomous Runs: Support for webhook, schedule, or Telegram triggers --- 📥 Input Examples | User Input | Agent Action | | --------------- | --------------------------------------------- | | btc | Returns 15m + 1h analysis for BTC | | eth 4h | Returns 4-hour swing data for ETH | | bnbusdt today | Full day snapshot with technicals + 24h stats | --- 🖥️ Telegram Output Sample 📊 BTC/USDT Market Summary 💰 Price: $62,400 📉 24h Stats: High $63,020 | Low $60,780 | Volume: 89,000 BTC 📈 1h Indicators: • RSI: 68.1 → Overbought • MACD: Bearish crossover • BB: Tight squeeze forming • ADX: 26.5 → Strengthening trend 📉 Support: $60,200 📈 Resistance: $63,800 --- 🛠️ Setup Instructions Create your Telegram Bot using @BotFather Add Bot Token in n8n Telegram credentials Add your GPT-4o or OpenAI-compatible key under HTTP credentials in n8n (Optional) Add your HTX API credentials if expanding to authenticated endpoints Deploy this main workflow using: ✅ Webhook (HTTP Request Trigger) ✅ Telegram messages ✅ Cron / Scheduled automation --- 🎥 Live Demo [](https://youtu.be/Crr41F8tr0Q?si=hZv_WRY2ZOA9-Y0V) --- 🧠 Internal Architecture | Component | Role | | ------------------ | -------------------------------------------------------- | | 🔄 Telegram Trigger | Entry point for external or manual signal | | 🧠 GPT-4o | Symbol + timeframe extraction + strategy generation | | 📊 Data Collector | Internal tools fetch price, indicators, order book, etc. | | 🧮 Reasoning Layer | Merges everything into a trading signal summary | | 💬 Telegram Output | Sends formatted HTML report via Telegram | --- 📌 Use Case Examples | Scenario | Outcome | | -------------------------------------- | ------------------------------------------------------- | | Auto-run every 4 hours | Sends new HTX signal summary to Telegram | | Human requests “eth 1h” | Bot replies with real-time 1h chart-based summary | | System-wide trigger from another agent | Invokes webhook and returns response to parent workflow | --- 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn
By Don Jayamaha JrSearch LinkedIn companies and add them to Airtable CRM
Search LinkedIn companies and add them to Airtable CRM Who is this for? This template is ideal for sales teams, business development professionals, and marketers looking to build a robust prospect database without manual LinkedIn research. Perfect for agencies, consultants, and B2B companies targeting specific business profiles. What problem does this workflow solve? Manually researching companies on LinkedIn and adding them to your CRM is time-consuming and error-prone. This automation eliminates the tedious process of finding, qualifying, and importing prospects into your database. What this workflow does This workflow automatically searches for companies on LinkedIn based on your criteria (keywords, size, location), retrieves detailed information about each company, filters them based on quality indicators (follower count and website availability), and adds new companies to your Airtable CRM while preventing duplicates. Setup Create a Ghost Genius API account and get your API key Configure HTTP Request nodes with Header Auth credentials (Name: "Authorization", Value: "Bearer yourapikey") Create an Airtable base named "CRM" with columns: name, website, LinkedIn, id, etc. Set up your Airtable credentials following n8n documentation Add your company search selection criteria to the “Set Variables” node. How to customize this workflow Modify search parameters in the "Set Variables" node to target different industries, locations, or company sizes Adjust the follower count threshold in the "Filter Valid Companies" node based on your qualification criteria Customize the Airtable fields mapping in the "Add Company to CRM" node to match your database structure Add notification nodes (Slack, Email) to alert you when new companies are added
By MatthieuMedical Q&A chatbot for urology using RAG with Pinecone and GPT-4o
Medical Q&A Chatbot for Urology using RAG with Pinecone and GPT-4o This template provides an AI-powered Q&A assistant for the Urology domain using Retrieval-Augmented Generation (RAG). It uses Pinecone for vector search and GPT-4o for conversational responses. 🧠 Use Case This chatbot is designed for clinics or medical pages that want to automate question answering for Urology-related conditions. It uses a vector store of domain knowledge to return verified responses. 🔧 Requirements ✅ OpenAI API key (GPT-4o or GPT-4o-mini) ✅ Pinecone account with an active index ✅ Verified Urology documents embedded into Pinecone ⚙️ Setup Instructions Create a Pinecone vector index and connect it using the Pinecone credentials node. Upload Urology-related documents to embed using the Create Embeddings for Urology Docs node. Customize the chatbot system message to reflect your medical specialty. Deploy this chatbot on your website or link it with Telegram via the chat trigger node. 🛠️ Components chatTrigger: Listens for user messages and starts the workflow. Medical AI Agent: GPT-based agent guided by domain-specific instructions. RAG Tool Vector Store: Fetches relevant documents from Pinecone using vector search. Memory Buffer: Maintains conversation context. Create Embeddings for Urology Docs: Encodes documents into vector format. 📝 Customization You can replace the knowledge base with any other medical domain by: Updating the documents stored in Pinecone. Modifying the system prompt in the AI Agent node. 📣 CTA This chatbot is ideal for clinics, medical consultants, or educational websites wanting a reliable AI assistant in Urology.
By HoangSPConversational Kubernetes management with GPT-4o and MCP integration
This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. Conversational Kubernetes Management with GPT-4o and MCP Integration This workflow enables you to manage Kubernetes clusters conversationally using OpenAI’s GPT-4o and a secure MCP (Model Context Protocol) server. It transforms natural language queries into actionable Kubernetes commands via a lightweight MCP API gateway — perfect for developers and platform engineers seeking to simplify cluster interaction. --- 🚀 Setup Instructions Import the Workflow Upload this template to your n8n instance. Configure Required Credentials OpenAI API Key: Add your GPT-4o API key in the credentials. MCP Client Node: Set the URL and auth for your MCP server. Test Kubernetes Access Ensure your MCP server is correctly configured and has access to the target Kubernetes cluster. --- 🧩 Prerequisites n8n version 0.240.0 or later Access to GPT-4o via OpenAI A running MCP server Kubernetes cluster credentials configured in your MCP backend --- ⚠️ Community Nodes Disclaimer This workflow uses custom community nodes (e.g., MCP Client). Make sure to review and trust these nodes before running in production. --- 🛠️ How It Works A webhook or chat input triggers the conversation. GPT-4o interprets the message and generates structured Kubernetes queries. MCP Client securely sends requests to your cluster. The result is returned and formatted for easy reading. --- 🔧 Customization Tips Tweak the GPT-4o prompt to match your tone or technical level. Extend MCP endpoints to support new Kubernetes actions. Add alerting or monitoring integrations (e.g., Slack, Prometheus). --- 🖼️ Template Screenshot --- 🧠 Example Prompts Show me all pods in the default namespace. Get logs for nginx pod in kube-system. List all deployments in staging. --- 📎 Additional Resources MCP Server on GitHub OpenAI Documentation n8n Docs --- Build smarter Kubernetes workflows with the power of AI !
By Reza GholizadeGenerate AI avatar videos with GPT-5 & publish to social media platforms
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automate Social Media with HeyGen and GPT-5: Publish Videos to TikTok, YouTube & Instagram --- 👥 Who is this for? This workflow is designed for: Content creators who want to scale their short-form video production Marketing teams seeking consistent and automated publishing pipelines Agencies managing multiple social accounts for clients Entrepreneurs looking to save time by automating repetitive content tasks --- 💡 What problem is this workflow solving? Publishing on multiple platforms like YouTube Shorts, TikTok, and Instagram is often: Time-consuming (manual editing, caption writing, uploads) Inconsistent (different requirements for each platform) Prone to delays (switching between tools) This workflow solves these issues by creating a fully automated video pipeline powered by GPT-5, HeyGen, and Blotato. --- ⚙️ What this workflow does Capture voice idea via Telegram Transcribe voice to text using OpenAI Whisper Generate a catchy title and caption with GPT-5 Create an AI avatar video with HeyGen Save and organize assets in Google Drive and Google Sheets Upload final video to Blotato Auto-publish to: YouTube Shorts TikTok Instagram (Optional: Facebook, X/Twitter, LinkedIn, Pinterest, Threads, Bluesky) Update logs in Google Sheets Send a Telegram confirmation once published --- 🧰 Setup Before using this workflow, ensure you have: A Telegram Bot connected to n8n for voice input An OpenAI API key for transcription (Whisper) and GPT-5 processing A HeyGen account & API key for avatar video generation A Google Drive & Google Sheets integration for storing assets and logs A Blotato account (Pro plan) with API access enabled Verified Community Nodes enabled in n8n Admin Panel Blotato node installed and credentials configured --- 🛠️ How to customize this workflow Prompts → Adjust GPT-5 prompts to match your brand voice and niche Avatars → Use custom avatars or voices via HeyGen configuration Platforms → Activate only the social nodes you need (e.g., focus on TikTok & YouTube Shorts) Approval steps → Add Telegram or Slack confirmation before publishing Analytics → Extend the workflow to track engagement data in Google Sheets, Airtable, or Notion --- This workflow turns a simple spoken idea into a viral-ready video — automatically generated, styled, and posted across your most important platforms. --- 📄 Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
By Dr. FirasCallForge - 01 - filter Gong calls synced to Salesforce by opportunity stage
Workflow Description Who is this for? This workflow is designed for sales and revenue teams using Gong and Salesforce to track and analyze sales calls. It helps automate the extraction, filtering, and preprocessing of Gong call data for further AI analysis. What problem is this solving? Sales teams often generate large amounts of call data, but not all calls are relevant for deeper analysis. This workflow filters calls based on predefined criteria, extracts relevant metadata, and formats the data before passing it to an AI processing pipeline. What this workflow does Triggers on new Gong calls synced to Salesforce every hour. Filters calls based on opportunity stage (Discovery or Meeting Booked). Retrieves Gong call details via API. Formats call data into a structured JSON object for AI processing. Passes the structured data to a Gong Call Preprocessor workflow for further insights. Setup Ensure that you have connected Salesforce and Gong APIs with valid credentials. Modify the Salesforce query in Get all custom Salesforce Gong Objects to match your organization’s requirements. Set the schedule trigger interval in the Run Hourly node if needed. Connect this workflow to an AI processing workflow to analyze call transcripts. Workflow Templates: CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion How to customize Change filtering logic: Adjust the opportunity stage filter (Check if Opportunity Stage is Meeting Booked or Discovery) to match your sales process. Modify data formatting: Add or remove fields in the Format call into correct JSON Object node to customize the output. Adjust trigger frequency: Change the Run Hourly node to run at a different interval if required.
By Angel MenendezAI-powered reservation reminder calls for restaurant with Twilio & Grok-4
🤖📞 This workflow automates the process of calling customers to remind them of their booking reservations using AI-generated messages and a Twilio phone number. It can easily be adapted for other venues. --- Key Benefits Time-Saving Automation: Eliminates the need for manual calls by staff, saving hours per week. Human-like AI Messages: Uses a custom language model to generate polite, natural phone messages tailored to each customer. Multi-Channel Integration: Google Sheets for reservation tracking. Twilio for automated calling. OpenRouter (or other LLMs) for generating speech content. Error Reduction: Ensures all customers receive reminders exactly on the reservation day, minimizing no-shows. Scalable: Easily adapts to growing reservation lists and more complex message logic. Suitable for restaurants, hairdressers, offices and any other business --- How It Works Trigger: The workflow can be triggered manually (via "When clicking ‘Execute workflow’) or automatically at 11 AM daily (via Schedule Trigger). Data Fetch: Retrieves today’s reservations from a Google Sheet, filtering rows where DATE = today and CALLED is empty. AI-Generated Call Script: For each reservation, the Secretary Agent (powered by OpenRouter’s Grok-4) generates a phone script using the guest’s name, time, and party size. Twilio Call: The script is sent to Twilio, which calls the guest’s phone number (from the sheet) and reads the message aloud using text-to-speech. Update & Loop: Marks the reservation as called (CALLED = "x") in the sheet and waits 2 minutes between calls to avoid rate limits. --- Set Up Steps Twilio Configuration: Sign up for Twilio, buy a phone number, and: Enable text-to-speech (set language to Italian). Configure geo permissions for the target country. Add credentials to the Twilio node (sender number in From field). Google Sheets Setup: Clone the Google Sheet template and ensure: Phone numbers include the international prefix (without "+"). Columns: DATE, TIME, NAME, N. PEOPLE, PHONE, CALLED. OpenRouter API: Connect the OpenRouter Chat Model node to your account (using Grok-4 or another model). Deploy: Activate the workflow and test with manual execution. Note: The workflow is currently inactive (active: false). Enable it after setup. ---- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By DavideEvaluation metric example: categorization
AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether a category matches the expected one. The workflow takes support tickets and generates a category and priority, which is then compared with the correct answers in the dataset. We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info Once the category is generated by the agent, we check whether it matches the expected one in the dataset Finally we pass this information back to n8n as a metric
By David Roberts