Workflow Templates

This n8n template automates the transformation of raw meeting notes into structured tasks and documents using GPT (or another model) , syncing them to Notion and TickTick via a Telegram bot. Use Cases Automate note-taking and formatting for daily standups, brainstorming sessions, or client calls. Reduce cognitive load by eliminating manual tracking of ideas and tedious formatting. Convert discussions into actionable tasks instantly with TickTick and structured notes in Notion. How It Works Capture Notes: Send raw meeting notes to a Telegram bot. AI Processing: The workflow sends the text to AI, which: Removes duplicates and extracts key points. Formats content into structured Markdown notes for Notion. Identifies tasks with deadlines (e.g., "- Prepare presentation (Responsible: John, Deadline: Friday)"). Task Parsing: Extracts task titles, removing metadata like "Responsible" and "Deadline." Review & Edit: The bot returns formatted notes and tasks for review in Telegram. Sync & Publish: Notes are published to a Notion database. Tasks are exported to TickTick via API. Confirmation: A Telegram reaction (e.g., 👌 emoji) confirms successful processing. Setup Instructions Set Up Telegram Bot: Create a Telegram bot via BotFather and obtain an API token. Add the token to the "Telegram Trigger" and "Send-Edited-Notes" nodes under credentials (telegramApi). Configure OpenAI: Obtain an OpenAI API key and add it to the "Edit-Notes" node (openAiApi credentials). Ensure the model is set to gpt-4.1-mini in the node parameters. Set Up Notion: Create a Notion database for notes (e.g., "Meetings"). Add the database ID to the "Create a Database Page" node (databaseId). Configure Notion API credentials (notionApi) in the node. Set Up TickTick: Obtain a TickTick API key and add it to the "Create a Task" node (tickTickOAuth2Api credentials). Specify your TickTick project ID in the node (projectId). Deploy Workflow: Ensure your n8n instance is self-hosted to support community nodes (TickTick, Notion). Activate the workflow in n8n. Test: Send a test message to the Telegram bot (e.g., "Discussed project timeline. Tasks: - Prepare slides (Responsible: Alice, Deadline: Friday)"). Verify that notes appear in Notion, tasks in TickTick, and a 👌 reaction in Telegram. Configuration Examples Telegram Trigger: { "parameters": { "updates": ["message"], "additionalFields": {} }, "credentials": { "telegramApi": { "id": "your-telegram-api-id", "name": "meeting notes" } } } OpenAI Prompt (in "Edit-Notes" node): Analyze the quick meeting notes from {{ $json.message.text }} Generate meeting notes and a task list in the following format:\nMeeting Notes:\n- [Note 1]\n- [Note 2]\n\nTasks:\n- [Task 1] \n- [Task 2] Notion Database Page { "parameters": { "resource": "databasePage", "databaseId": "your-notion-database-id", "title": "MN {{ $now }}", "blockUi": { "blockValues": [ { "textContent": "{{ $json.message.text }}" } ] } } } Requirements Requires an OpenAI API key (or another model). APIs: Pre-configured Notion and TickTick API credentials are required. The template includes setup guides. Setup: Uses community nodes, requiring a self-hosted n8n instance. Customizing This Workflow Replace the Telegram bot with a webhook or form for alternative inputs (e.g., mobile apps). Modify the OpenAI prompt in the "Edit-Notes" node to customize note and task formats. Add filters in the "Split Notes and Tasks" node to prioritize tasks (e.g., ++#urgent++). Integrate Google Calendar via an additional HTTP Request node to auto-set deadlines based on text (e.g., "by Friday").

This n8n template demonstrates how you can leverage existing support site search to power your Support Chatbots and agents. Building a support chatbot need not be complicated! If building and indexing vector stores or duplicating data isn't necessarily your thing, an alternative implementation of the RAG approach is to leverage existing knowledge-bases such as support portals. In this way, document management and maintenance of your support agent is significantly reduced. Disclaimer: This template example uses AcuityScheduling's help center website but is not associated, supported nor endorsed by the company. How it works A simple AI agent is connected with chat trigger to receive user queries. The AI agent is instructed to fetch information from the knowledge-base via the attached custom workflow tool (aka "knowledgebase tool"). There is no step to replicate the entire support articles database into a vector store. You may choose not too because of time, cost and maintainence involved. Instead, the tool leverages the existing support portal's search API to retrieve knowledge-base articles. Finally, the search results are formatted before sending an aggregated response back to the agent. How to use? Customise the subworkflow to work with your own support portal API and format accordingly. Try the following queries How do I connect my icloud to acuityScheduling? How do I download past invoices for my Acuity account? Requirements OpenAI for LLM. If your organisation's APIs require authorisation, you may need to add custom credentials as necessary. Customising this workflow Add additional tools to reach other parts of your internal knowledgebase. Not using OpenAI? Feel free to swap but ensure the LLM has tools/function calling support.

Your Landing Page is Leaking Sales—Here’s How to Fix It in Seconds Visitors land on your page. But instead of converting, they bounce. Why? Something’s broken. Something’s missing. But what? ❌ Is your CTA too weak? ❌ Is your messaging unclear? ❌ Is your design creating friction? You know something is off, but don’t know what. What if you could get an instant, expert-level report on exactly what to fix? This workflow will do an AI Analysis of your landing page, provide a CRO Audit, so you can optimize your landing page. Who is This For? SaaS Founders & Startups**: Stop leaving money on the table. Make every visitor count. Marketers & Growth Experts**: Turn landing pages into high-converting assets. E-commerce & Lead Gen Businesses**: More conversions = more revenue. How It Works Paste your URL Get an instant roast + fix list Implement changes & watch conversions jump The workflow scrapes the url you input, gets the htlm source code of the landing page, and sends it to OpenAI AI Agent. The Agent makes a deep analysis, roasts the landing page, and provides 10 Conversion Rate Optimization Tips to improve your landing page. Setup Guide You will need OpenAI Credentials with an API Key to run the workflow. The workflow is using the OpenAI-o1 model to deliver the best results. It costs between $0.20/0.30 per run. You can adjust the prompt to your wish in the AI Agent parameters. Once the workflow has been completed, select Logs to get a readable version. Below is an example.

This workflow is designed to translate SRT subtitle files from one language to another using Google Translate. The workflow follows these main steps: Accept an SRT file upload and target language selection Extract and parse the SRT file content Split the content into translatable segments Translate each segment using Google Translate Reassemble the translated content into a proper SRT format Return the translated file to the user You'll need a Google Console Cloud account to access the Translate API. Who is this for? This workflow is designed for content creators, video editors, translators, and anyone who needs to translate subtitle files (.srt) from one language to another. It's particularly useful for those working with international content, educational materials, or preparing videos for global audiences. What problem does this workflow solve? Translating subtitle files manually is time-consuming and error-prone. Professional translation services can be expensive, especially for multiple videos or long content. This workflow automates the translation process while maintaining the proper SRT format including timestamps and subtitle numbering. Setup Set up Google Translate credentials: -- Create a Google Cloud project and enable the Google Translate API -- Create OAuth credentials and configure them in the Google Translate node Customize language options: -- The default workflow includes English (EN) and Japanese (JP) options -- Add more language options by editing the dropdown field in the "Receive SRT File to Translate" node -- Use standard language codes that Google Translate supports Add more languages: -- Edit the form trigger node to include additional language options in the dropdown

How the sequence works: A "Schedule Trigger" node activates the automation at a defined schedule. An "Airtable" node will search for previously posted questions in your question database. Airtable Base Template: here An "Aggregate" node will take all the questions from Airtable and compress them to a single output. ChatGPT, or a model of your choice, will generate a discussion question based on the options in the system prompt. The discussion question will be posted to the subreddit of your choice by the "Reddit" node. You can choose between a text, image, or link post! The recently-posted discussion question will then be uploaded to your Airtable base using the "Airtable" node. This will be used to prevent ChatGPT from creating duplicate questions. Setup Steps The setup process will take about 5 minutes. An Airtable base template is also pre-made for you here: https://airtable.com/app6wzQqegKIJOiOg/shrzy7L9yv8BFRQdY Set the recurrence in the "Schedule" node Create an Airtable account, you can use the link here. Get an Airtable personal access token here. Configure the "Get Previous Discussions" Airtable node. Configure the options in brackets in the "Generate New Discussion" node. Set the desired subreddit to post to and the post type(text, image, or link) in the "Post Discussion" node. Configure the "Create Archived Discussion" node to map to the Airtable base(required) and specific subreddit(optional).

This n8n template watches a Gmail inbox for support messages and creates an equivalent issue item in Linear. How it works A scheduled trigger fetches recent Gmail messages from the inbox which collects support requests. These support requests are filtered to ensure they are only processed once and their HTML body is converted to markdown for easier parsing. Each support request is then triaged via an AI Agent which adds appropriate labels, assesses priority and summarises a title and description of the original request. Finally, the AI generated values are used to create an issue in Linear to be actioned. How to use Ensure the messages fetched are solely support requests otherwise you'll need to classify messages before processing them. Specify the labels and priorities to use in the system prompt of the AI agent. Requirements Gmail for incoming support messages OpenAI for LLM Linear for issue management Customising this workflow Consider automating more steps after the issue is created such as attempting issue resolution or capacity planning.

AI Research Assistant via Telegram (GPT-4o mini + DeepSeek R1 + SerpAPI) 👥 Who’s it for This workflow is perfect for anyone who wants to receive AI-powered research summaries directly on Telegram. Ideal for people asking frequent product, tech, or decision-making questions and want up-to-date answers sourced from the web. 🤖 What it does Users send a question via Telegram. An AI agent (DeepSeek R1) reformulates and understands the intent, while a second agent (GPT-4o mini) performs live research using SerpAPI. The most relevant answers, including links and images, are delivered back via Telegram. ⚙️ How it works 📲 Telegram Trigger – Starts when a user sends a message to your Telegram bot. 🧠 DeepSeek R1 Agent – Understands, clarifies, or reformulates the user query. 🧠 Research AI Agent (GPT-4o mini + SerpAPI) – Searches the web and summarizes the best results. 📤 Send Telegram Message – Sends the response back to the same user. 📋 Requirements Telegram bot (via BotFather) with API token set in n8n credentials OpenAI account with API key and balance for GPT-4o mini SerpAPI account (100 free searches/month) with API key DeepSeek account with API key and balance 🛠️ How to set up Create your Telegram bot using BotFather and connect it using the Telegram Trigger node Set up DeepSeek credentials and add a Chat Model AI Agent node using DeepSeek R1 to reformulate the user’s question Set up OpenAI credentials and add a second ChatGPT AI Agent node using GPT-4o mini In the GPT-4o node, enable the SerpAPI Tool and add your SerpAPI API key Pass the reformulated question from DeepSeek to the GPT-4o agent for live search and summarization Format the response (text, links, optional images) Send the final reply to the user using the Telegram Send Message node Ensure your n8n instance is publicly accessible Test the workflow by sending a message to your Telegram bot ✅

Personalized Tour Package Recommendations via n8n + Pinecone + Lovable UI I've created an intelligent Travel Itinerary Planner that connects a Lovable front-end UI with a smart backend powered by n8n, Pinecone, and OpenAI to deliver personalized tour packages based on natural language queries. What It Does Users type in their travel destination and duration (e.g., "Paris 5 days trip" or "Bali Trip for 7 Days, would love water sports, adventures and trekking included, also some historical monuments") through a Lovable UI. This triggers a webhook in n8n, which processes the request, searches vectorized tour data in Pinecone, and generates a personalized itinerary using OpenAI’s GPT. The results are then structured and sent back to the frontend UI for display in an interactive, reorderable format. Workflow Architecture Lovable UI ➝ Webhook ➝ Tour Recommendation Agent ➝ Vector Search ➝ OpenAI Response ➝ Structured Output ➝ Response to Lovable Tools & Components Used Webhook Acts as the entry point between the Lovable frontend and n8n. Captures the user query (destination, duration) and forwards it into the workflow. OpenAI Chat Model To interpret the user query. To generate a user-friendly, structured tour package from the matched results. Simple Memory Keeps chat state and context for follow-up queries (extendable for future features like multi-step planning or saved itineraries). Question Answering with Vector Store Searches vector embeddings of pre-loaded tour data. Finds the most relevant tour packages by comparing query embeddings. Pinecone Vector Store Stores tour packages and activity data in vectorized format. Enables fast and scalable semantic search across destinations, themes (e.g., "adventure", "cultural"), and duration. OpenAI Embeddings Embeds all tour and activity documents stored in Pinecone. Converts input user queries into embedding vectors for semantic search. Structured Output Parser Parses the final OpenAI-generated response into a consistent, frontend-consumable JSON format. Frontend (Lovable UI) User types in destination or their travel package needs in the Tour Search. Lovable queries the n8n workflow. Displays beautifully structured, editable itineraries. How to Set It Up Webhook Setup in n8n Create a POST webhook node. Set Webhook URL and connect it with Lovable frontend. Pinecone & Embeddings Convert your static tour package documents (PDFs, JSON, CSV, etc.) into embeddings using OpenAI. Store the embeddings in a Pinecone namespace (e.g., kuala-lumpur-3-days). Configure “Answer with Vector Store” Tool Connect the tool to your Pinecone instance and pass query embedding for matching. Connect to OpenAI Chat Use the GPT model to process query + context from Pinecone to generate an engaging itinerary description. Optionally chain a second model to format it into UI-consumable output. Output Parser & Return Use Structured Output Parser to parse the response and pass it to Respond to Webhook node for UI display. Ideal Use Cases Smart itinerary planning for OTAs or DMCs Personalized travel recommendations in chatbots or apps Travel advisors and agents automating package generation Benefits Highly relevant, contextual travel suggestions Natural query understanding via OpenAI Seamless frontend-backend integration via Webhook If you’re building personalized experiences for travelers using AI, give this approach a try! Let me know if you’d like the JSON for this workflow or help setting up the Pinecone data pipeline.

This n8n template demonstrates how to calculate the evaluation metric "RAG document groundedness" which in this scenario, measures the ability to provide or reference information included only in retrieved vector store documents. The scoring approach is adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness How it works This evaluation works best for an agent that requires document retrieval from a vector store or similar source. For our scoring, we need to collect the agent's response and the documents retrieved and use an LLM to assess if the former is based off the latter. A key factor is to look out information in the response which is not mentioned in the documents. A high score indicates LLM adherence and alignment whereas a low score could signal inadequate prompt or model hallucination. Requirements n8n version 1.94+ Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

Document-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 Connect your WhatsApp Cloud API account (Meta) Add your Google account and grant access to the Doc containing your company info Choose your AI model (ChatGPT/OpenAI or Gemini) Paste your document ID into the Google Docs node Connect your WhatsApp webhook to Meta (only takes 5 minutes) 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

It allows you to automate candidate retrieval and onboarding in your HR processes. How it works It monitors a Gmail address for new emails with a PDF attachment It expects the PDF to be a candidate’s CV, extracts the text using OCR, and then structures the data using ChatGPT Once the data is processed, it connects to Notion and adds (or updates) an entry in the specified database How to use Configure your Gmail account and provide your ChatGPT API key Provide an API key for the OCR service in a variable named OCR_SPACE_API_KEY Connect your Notion account Once everything is configured, the workflow will monitor your inbox for new emails. Just send an email with a PDF attachment to the configured address Requirements In addition to Gmail, ChatGPT, and Notion, the system uses a third-party OCR API (OCR SPACE). You’ll need to create an account and obtain an API key You must map the fields returned by ChatGPT to the Notion database, or use the same field names we are using Customising It should be easy to replace Notion with PostgreSQL or another database if needed

This workflow automatically transcribes audio files, translates the content between languages, and generates natural-sounding speech from the translated text - all in one seamless process. Who's it for Content creators, educators, and businesses needing to make their audio content accessible across language barriers. Perfect for translating podcasts, voice messages, lectures, or any audio content while preserving the spoken format. How it works The workflow receives an audio file through a webhook, transcribes it using OpenAI's Whisper, translates and structures the text with GPT-4, generates new audio in the target language, and stores it in S3 for easy access. The entire process takes seconds and returns both the transcribed/translated text and a URL to the translated audio file. How to set up Configure OpenAI credentials - Add your OpenAI API key for Whisper transcription and GPT-4 translation Set up AWS S3 - Create a bucket with public read permissions for audio storage Update configuration - Replace 'YOUR-BUCKET-NAME' with your actual S3 bucket name Activate webhook - Deploy and copy your webhook URL for receiving audio files Send a POST request with: Binary audio file (as 'audiofile') Languages parameter (e.g., "English, Spanish") Requirements OpenAI API account with access to Whisper and GPT-4 AWS account with S3 bucket configured Basic understanding of webhooks and API requests How to customize Add language detection** - Automatically detect source language if not specified Customize voice settings** - Adjust speech speed, pitch, or select different voices Add file validation** - Implement size limits and format checks Enhance security** - Add webhook authentication and rate limiting Extend functionality** - Add subtitle generation or multiple output formats