Task: Create a simple API endpoint using the Webhook and Respond to Webhook nodes Why: You can prototype or replace a backend process with a single workflow Main use cases: Replace backend logic with a workflow

Jonathan

AI key concepts

AI agent chat

n8n Team

AI chat with any data source (using the n8n workflow tool)

David Roberts

Chat with OpenAI Assistant (by adding a memory)

David Roberts

Use an open-source LLM (via HuggingFace)

n8n Team

+10

Chat with PDF docs using AI (quoting sources)

David Roberts

AI agent that can scrape webpages

Eduard

Featured AI templates

Auto-label incoming Gmail messages with AI nodes

This workflow uses AI to analyze the content of every new message in Gmail and then assigns specific labels, according to the context of the email. Default configuration of the workflow includes 3 labels: „Partnership” - email about sponsored content or cooperation, „Inquiry” - email about products, services, „Notification” - email that doesn't require response. You can add or edit labels and descriptions according to your use case. 🎬 See this workflow in action in my YouTube video about automating Gmail. Gmail trigger performs polling every minute for new messages (you can change the trigger interval according to your needs). The email content is then downloaded and forwarded to an AI chain. 💡 The prompt in the AI chain node includes instructions for applying labels according to the email content - change label names and instructions to fit your use case. Next, the workflow retrieves all labels from the Gmail account and compares them with the label names returned from the AI chain. Label IDs are aggregated and applied to processed email messages. ⚠️ Label names in the Gmail account and workflow (prompt, JSON schema) must be the same. Set credentials for Gmail and OpenAI. Add labels to your Gmail account (e.g. „Partnership”, „Inquiry” and „Notification”). Change prompt in AI chain node (update list of label names and instructions). Change list of available labels in JSON schema in parser node. Optionally: change polling interval in Gmail trigger (by default interval is 1 minute). If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.

Oskar

Compose reply draft in Gmail with OpenAI Assistant

Oskar

ChatGPT Automatic Code Review in Gitlab MR

assert

Write a WordPress post with AI (starting from a few keywords)

Giulio

+11

Suggest meeting slots using AI

n8n Team

Popular AI integrations

Chat with a Google Sheet using AI

David Roberts

Chat with OpenAIs GPT via a simple Telegram Bot

Mike

+10

Chat with PDF docs using AI (quoting sources)

David Roberts

Slack chatbot powered by AI

n8n Team

Trending $user.role templates

Trending AI templates

Verify and enrich your new leads and contacts

Scrape recent news about a company before a call

Milorad Filipović

Verify emails & enrich new form leads and save them to HubSpot

Niklas Hatje

Enrich new leads in Pipedrive and send an alert to Slack for high-quality ones

Niklas Hatje

Automate your outreach and follow-ups

Send follow-ups using Gmail to Hubspot contacts

Mutasem

Reach out via Email to new form submissions that meet a certain criteria

Niklas Hatje

Automatically email great leads when they submit a form and record in HubSpot

Mutasem

Gmail campaign sender: Bulk-send emails and follow up automatically if no reply

David Roberts

Featured templates

Allow Users to Send a Sequence of Messages to an AI Agent in Telegram

When creating chatbots that interface through applications such as Telegram and WhatsApp, users can often sends multiple shorter messages in quick succession, in place of a single, longer message. This workflow accounts for this behaviour. This workflow allows users to send several messages in quick succession, treating them as one coherent conversation instead of separate messages requiring individual responses. When messages arrive, they are stored in a Supabase PostgreSQL table The system waits briefly to see if additional messages arrive If no new messages arrive within the waiting period, all queued messages are: Combined and processed as a single conversation Responded to with one unified reply Deleted from the queue Create a table in Supabase called message_queue. It needs to have the following columns: user_id (uint8), message (text), and message_id (uint8) Add your Telegram, Supabase, OpenAI, and PostgreSQL credentials Activate the workflow and test by sending multiple messages the Telegram bot in one go Wait ten seconds after which you will receive a single reply to all of your messages Change the value of Wait Amount in the Wait 10 Seconds node in order to to modify the buffering window Add a System Message to the AI Agent to tailor it to your specific use case Replace the OpenAI sub-node to use a different language model