Workflow Templates

This n8n template watches an outlook shared inbox for support messages and creates an equivalent issue item in JIRA. How it works A scheduled trigger fetches recent Outlook messages from an shared 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 JIRA 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 Outlook for incoming support OpenAI for LLM JIRA for issue management Customising this workflow Consider automating more steps after the issue is created such as attempting issue resolution or capacity planning.

Make OpenAI Citation for File Retrieval RAG Use case In this example, we will ensure that all texts from the OpenAI assistant search for citations and sources in the vector store files. We can also format the output for Markdown or HTML tags. This is necessary because the assistant sometimes generates strange characters, and we can also use dynamic references such as citations 1, 2, 3, for example. What this workflow does In this workflow, we will use an OpenAI assistant created within their interface, equipped with a vector store containing some files for file retrieval. The assistant will perform the file search within the OpenAI infrastructure and will return the content with citations. We will make an HTTP request to retrieve all the details we need to format the text output. Setup Insert an OpenAI Key How to adjust it to your needs At the end of the workflow, we have a block of code that will format the output, and there we can add Markdown tags to create links. Optionally, we can transform the Markdown formatting into HTML.

Who is this for? This workflow is ideal for SEO specialists, web designers, and digital marketers who want to quickly draft effective landing page layouts by referencing established competitors. It suits users who need a fast, structured starting point for web design while ensuring competitive relevance. What problem is this workflow solving? / Use case Designing a high-converting landing page from scratch can be time-consuming. This workflow automates the process of analyzing a competitor’s website, identifying essential sections, and producing a tailored layout—helping users save time and improve their website’s effectiveness. What this workflow does The workflow fetches and analyzes your chosen competitor’s landing page, using web scraping and structure-detection nodes in n8n. It identifies primary sections like hero banners, service highlights, testimonials, and contact forms, and then generates a simplified, customizable layout suitable for wireframing or initial design. Setup Prepare your unique services and target audience profile for customization later. Gather the competitor’s landing page URL you wish to analyze. Run the workflow, inputting your competitor’s URL when prompted. How to customize this workflow to your needs After generating the initial layout, adapt section names and content blocks to highlight your services and brand messaging. Add or remove sections based on your objectives and audience insights. Integrate additional nodes for richer analysis, such as keyword extraction or design pattern detection, to tailor the output further.

This n8n workflow leverages a Telegram Message Trigger to activate an intelligent AI Agent capable of processing both text and voice messages. When a user sends a message in text or in voice format, the workflow captures and transcribes it (if necessary), then passes it to the AI Agent for understanding and response generation. To enhance user experience, the bot also displays a typing indicator while processing requests, simulating a natural, human-like interaction. Key Features Multi-Modal Input: Supports both text messages and voice notes from users. Real-Time Interaction: Shows a “typing…” action in Telegram while the AI processes the input. AI Agent Integration: Provides intelligent, context-aware, and conversational responses. Seamless Feedback Loop: Replies are sent directly back to the user within Telegram for smooth interaction. How It Works The workflow triggers whenever a message or voice note is received on Telegram. If the input is a voice note, the workflow transcribes it into text. The text input is sent to the AI Agent for processing. While processing, the bot sends a typing indicator to the user. Once the AI generates a response, the workflow sends it back to the user in Telegram. Setup Instructions Create a Telegram Bot: Use @BotFather to create a bot and obtain your bot token. Configure n8n Credentials: Add Telegram API credentials in n8n with your bot token. Add credentials for any speech-to-text service used for voice transcription (e.g., Open AI Transcribe A Recording). Import the Workflow: Import this workflow into your n8n instance. Update all credential nodes to use your Telegram and transcription service credentials. Set Webhook URLs: Ensure Telegram webhook is set properly for your bot to receive messages. Make sure your n8n instance is publicly accessible for Telegram callbacks. Test the Workflow: Send text messages and voice notes to your Telegram bot and observe the AI responses. Customization Guidance Add new message handlers: Extend the workflow to handle additional message types (images, documents, etc.). Improve transcription: Swap or add speech-to-text services for better accuracy or language support. Enhance AI Agent: Customize prompts and context management to tailor the AI’s personality and responses. AI Model Flexibility: Swap between different AI models (e.g., GPT-4, Claude, or custom LLMs) based on task type, cost, or performance preferences. Tool-Based Control: Add custom tools to the AI Agent such as calendar access, Notion, Google Sheets, web search, database queries, or custom APIs—allowing for dynamic, multi-functional agents Security and Implementation Notes The Telegram node manages message reception and sending but does not directly handle AI processing. Voice transcription requires integration with external APIs; secure those credentials in n8n and monitor usage. To simulate typing, the workflow uses Telegram’s “sendChatAction” API method, providing users with feedback that the bot is processing. Ensure your AI API keys and Telegram tokens are securely stored in n8n credentials and not exposed in workflows or logs. Benefits Handles natural conversational inputs with text or voice. Provides a smooth, engaging user experience via typing indicators. Easy integration of advanced AI conversational agents with Telegram. Flexible for personal assistants, helpdesks, or interactive chatbots.

Transform your BeyondPresence video agent conversations into comprehensive insights by automatically analyzing each call with AI and organizing 35+ data points in Google Sheets. This template helps customer success, support, and training teams save 30+ minutes per call on documentation while ensuring no critical action items or insights are missed. How it works Webhook receives** completed call data from BeyondPresence including full transcript Data validation** ensures quality and adds enriched metadata (duration, time calculations) AI analysis** (GPT-4) extracts action items, sentiment, decisions, and recommendations Parse response** handles the AI output and structures it for sheets Auto-append** to Google Sheets with 35+ insights per call organized beautifully Set up steps Copy our Google Sheets template - One click! Get pre-formatted sheet: BeyondPresence Call Analytics Template Connect accounts - Add OpenAI API key and Google Sheets OAuth2 Configure webhook - Copy URL from n8n to BeyondPresence Settings → Webhooks Customize AI prompt (optional) - Adjust analysis focus for your use case Test with a call - Make a test call and watch insights appear! Setup time: 5-10 minutes Requirements: BeyondPresence account, OpenAI API key, Google account

This n8n template demonstrates how to calculate the evaluation metric "Similarity" which in this scenario, measures the consistency of the agent. The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_similarity.py How it works This evaluation works best where questions are close-ended or about facts where the answer can have little to no deviation. For our scoring, we generate embeddings for both the AI's response and ground truth and calculate the cosine similarity between them. A high score indicates LLM consistency with expected results whereas a low score could signal 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

How it works Automates the retrieval of Calvin and Hobbes daily comics. Extracts the comic image URL from the website. Translates comic dialogues to English and Korean. Posts the comic and translations to Discord daily. Set up steps Estimated setup time: ~10-15 minutes. Use a Schedule Trigger to automate the workflow at 9 AM daily. Add nodes for parameter setup, HTTP request, data extraction, and integration with Discord. Add detailed notes to each node in the workflow for easy understanding.

How it works • Allows users to manage their Google Calendar via WhatsApp using natural language • Handles event creation, updates, deletions, availability checks, and agenda overviews • AI agent interprets the user’s message and triggers the appropriate calendar action • Responses are sent back to the user via WhatsApp, with confirmation or schedule info Set up steps • Set up a WhatsApp Business Cloud account and configure your webhook • Connect your Google Calendar using n8n credentials • Deploy OpenAI API key for natural language understanding • Link each calendar action (create, update, delete, search) to the TimePilot agent • Customize confirmation messages and automate reply formatting Note: More detailed configuration and custom logic are described inside sticky notes within the workflow.

Who is this for This workflow is perfect for teams and individuals who manage extensive data in Notion and need a quick, AI-powered way to interact with their databases. If you're looking to streamline your knowledge management, automate searches, and get faster insights from your Notion databases, this workflow is for you. It’s ideal for support teams, project managers, or anyone who needs to query specific data across multiple records or within individual pages of their Notion setup. Check out the Notion template this Assistant is set up to use: https://www.notion.so/templates/knowledge-base-ai-assistant-with-n8n How it works The Notion Database Assistant uses an AI Agent built with Retrieval-Augmented Generation (RAG) to query this Knowledge Base style Notion database. The assistant can search across multiple properties like tags or question and retrieves content from inside individual Notion pages for additional context. Key features include: Querying the database with flexible filters. Searching within individual Notion pages and extracting relevant blocks. Providing a reference link to the exact Notion pages used to inform its responses, ensuring transparency and easy verification. This assistant uses two HTTP request tools—one for querying the Notion database and another for pulling data from within specific pages. It streamlines knowledge retrieval, offering a conversational, AI-driven way to interact with large datasets. Set up Find basic set up instructions inside the workflow itself or watch a quickstart video 👇

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 easy it is to build an Outlook Calendar Assistant powered by an AI agent equipped with Tools. For teams using Outlook Calendar and Slack who need easier calendar management, this workflow can be a great first step to introducing powerful AI tools into your daily activities. How it works A Slack Trigger node is configured to catch "bot mentions" events in a designated channel. The message is parsed using the Edit fields node to extract only the required attributes of the event. An AI Agent equipped with Outlook Calendar Tools enables question and answer capability for the organisation's shared calendars and events. The AI agent's response is sent back to Slack as a reply to the user's query. How to use The workflow is triggered via @mention-ing the bot followed by the query. eg. "@bot how many meetings does Paul have to attend to this week?" To start listening to real mentions, you must activate the workflow and set it to production mode. You must use the production webhook URL for the event subscription. Some sample queries to try "What's included in the product team's sprint demo this week?" "Who's booked room 7 for this Thursday?" "When is Jim & Nik's sales meeting with Microsoft?" Requirements Slack for Chat and Trigger. To get connected to Slack, see the official n8n docs for Slack Credentials. Outlook for Agent Tools To get connected to Outlook, see the official n8n docs for Outlook Credentials. Customising this workflow Not using Slack? This template can be modified to work with Teams but requires a little more configuration. Agents can have any number of tools but an overloaded agent is prone to confusion! If this happens, try splitting into multiple agents serving separate needs.

This guide will show you how to use a workflow as a reusable tool in n8n, such as integrating an AI Agent or other specialized processes into your workflows. By the end of this example, you'll have a simple, reusable workflow that can be easily plugged into larger projects, making your automations more efficient and scalable. With this approach, you can create reusable workflows like "Scrape a Page," "Search Brave," or "Generate an Image," which you can then call whenever needed. While n8n makes it easy to build these workflows from scratch, setting them up as reusable components saves time as your automations grow in complexity. Setup Add the "Execute Workflow Trigger" node Add the node(s) to perform the desired tasks in the workflow Add a final "Set" or "Edit Fields" node at the end to ensure all external workflows return a consistent output format Details In this example, the "Execute Workflow Trigger" expects input in the following JSON format: [ { "query": { "url": "https://en.wikipedia.org/wiki/some_info" } } ] Once your external workflow is ready, you can instruct the AI Agent to use this tool by connecting it to the external workflow. Set up the schema type to "Generate from JSON Example" using this structure: { "url": "URL_TO_GET" } Finally, ensure your external workflow includes a "Set" or "Edit Fields" node at the end to define the response format. This helps keep the outputs of your reusable workflows consistent and predictable.