Workflow Templates

Video walkthrough https://www.youtube.com/watch?v=OwIFK-r-NtQ Summary of agent This agent can write and rewrite its own rules, allowing you to mold its behavior. It receives rules from a database as system instructions and has tools to create, edit, or delete them. This is a great baseline for new agent builds. You can tell it things like "Next time, use present tense when talking about this subject" and it will use a tool to save this as a rule, then receive that instruction in all future iterations. How to start using it Option 1: With a Postgres database (e.g., Supabase) Supabase Schema: Create a table (e.g., agent_rules) with the following columns: id: bigint (Primary Key, auto-incrementing) created_at: timestamp with time zone (Default: now()) rule_text: text agent: text Workflow Updates: Update the Postgres credentials in the "Get rules from database," "Insert rule into database," and "Execute query on rule database" nodes. Update the agent value (currently 'TestAgent') in the "Get rules from database" and "Insert rule into database" nodes if you want a different agent name. Update the Anthropic API credentials. Option 2: With Google Sheets Google Sheet Setup: Create a Google Sheet with columns for rule_text and agent. Workflow Updates: Example Google Sheets nodes are included. You will need to: Connect your Google Sheets credentials. Select your Google Sheet (with rule_text and agent columns) in all relevant Google Sheets nodes. Replace the existing Postgres nodes ("Get rules from database", "Insert rule into database", "Execute query on rule database") with the configured Google Sheets nodes. Update the agent value (currently 'TestAgent') in the Google Sheets nodes if you want a different agent name. Update the Anthropic API credentials. Agent Instructions: Update the agent's system message and remove the database schema section as it is no longer relevant

This workflow automatically checks the status of your websites using UptimeRobot API. If any site is down or unstable, it will: Generate a natural-language alert message using GPT-4o Push the message to a LINE group (with funny IT-style encouragement) Log all DOWN status entries into your Supabase database Wait 30 minutes before repeating 🔧 How It Works Schedule Trigger – Runs on a fixed interval (every few minutes). UptimeRobot Node – Fetches website monitor data. Code Node (Filter) – Filters only websites with status 8 (may be down) or 9 (down). IF Node – If any site is down, proceed. LangChain LLM Node – Formats alert with a humorous message using GPT-4o. Line Notify (HTTP Request) – Sends the alert to your LINE group. Loop Over Items – Loops through all monitors. Filter Down (Status = 9) – Selects only “fully down” sites. Supabase Node – Logs these into synlora_uptime_down table. Wait Node – Delays next alert by 30 minutes to avoid spamming. ⚙️ Setup Steps Required: 🔗 UptimeRobot API Key 📲 LINE Channel Access Token and Group ID 🧠 OpenAI Key (GPT-4o Mini) 🗃️ Supabase Project & Table Step-by-step: Go to UptimeRobot → Get API key and ensure monitors are set up. Create a Supabase table with fields: website, status, uptime_id. Create a LINE Messaging API bot, join it to your group, and get: Access Token Group ID (userId or groupId) Add your OpenAI API Key for GPT-4o Mini (or switch to your preferred LLM). Import the workflow JSON into n8n. Set credentials in all necessary nodes. Activate the workflow.

Automating LinkedIn Enrichment and ICP Scoring Use Case This automation enriches a person’s data using LinkedIn and calculates an Ideal Customer Profile (ICP) score based on their professional presence. It is particularly useful for lead qualification, contact research, and targeted outreach. What This Automation Does The automation processes the following input parameters: Person Name**: Full name of the individual. Work Email**: Business email address to validate corporate identity. Airtop Profile (connected to Linkedin)**: A LinkedIn-authenticated Airtop Profile for enrichment. How It Works Email Filtering: Checks if the email is corporate (excludes free and personal domains). LinkedIn Profile Discovery: Searches and verifies the correct LinkedIn URL using Airtop. Data Enrichment: Extracts professional details from the LinkedIn profile. ICP Scoring: Calculates an ICP score based on extracted data and profile context. Merge Outputs: Consolidates enriched profile data and ICP results into a single output. Setup Requirements Airtop API Key An Airtop Profile authenticated on LinkedIn. Next Steps Combine with CRM Integration**: Push enriched and scored data into CRMs like HubSpot or Salesforce. Batch Processing**: Automate for lists of leads using Airtop + n8n or Airtop SDK. Scoring Customization**: Adjust scoring logic to reflect your ideal customer attributes more precisely. Read more about data enrichment and ICP scoring

This n8n template shows you how to connect Github's Free Models to your existing n8n AI workflows. Whilst it is possible to use HTTP nodes to access Github Models, The aim of this template is to use it with existing n8n LLM nodes - saves the trouble of refactoring! Please note, Github states their model APIs are not intended for production usage! If you need higher rate limits, you'll need to use a paid service. How it works The approach builds a custom OpenAI compatible API around the Github Models API - all done in n8n! First, we attach an OpenAI subnode to our LLM node and configure a new OpenAI credential. Within this new OpenAI credential, we change the "Base URL" to point at a n8n webhook we've prepared as part of this template. Next, we create 2 webhooks which the LLM node will now attempt to connect with: "models" and "chat completion". The "models" webhook simply calls the Github Model's "list all models" endpoint and remaps the response to be compatible with our LLM node. The "Chat Completion" webhook does a similar task with Github's Chat Completion endpoint. How to use Once connected, just open chat and ask away! Any LLM or AI agent node connected with this custom LLM subnode will send requests to the Github Models API. Allowing your to try out a range of SOTA models for free. Requirements Github account and credentials for access to Models. If you've used the Github node previously, you can reuse this credential for this template. Customising this workflow This template is just an example. Use the custom OpenAI credential for your other workflows to test Github models. References https://docs.github.com/en/github-models/prototyping-with-ai-models https://docs.github.com/en/github-models

Mistral OCR is a super convenient way to parse and extract data from multi-page PDFs or single images using AI. What makes it special and differs it from the competition is that Mistral OCR also performs document page splitting and markdown conversion. This helps reduce dependencies required for document parsing workflows where tools like StirlingPDF. Read the official documentation on Mistral OCR API here: https://docs.mistral.ai/capabilities/document/#tag/ocr/operation/ocr_v1_ocr_post How it works To access Mistral-OCR, you'll need to use Mistral Cloud API via the HTTP request node Mistral OCR can only accept 2 file types: PDF and Image. Here, we use 2 different request to the Mistral-OCR API to parse a bank statement PDF and an screenshot of a bank statement to extract the tables. Next, we explore a more secure method of uploading documents to the Mistral OCR API by using Mistral's cloud storage. In example 2, we first store a copy of our documents to Mistral cloud and then generate a signed URL to retreive the file before sending it to Mistral OCR. This ensures the file is not accessible publicly and protects it from unauthorised access. Finally, another way to use Mistral-OCR is via document understanding. This allows you to ask questions about the document rather than extract contents from it. In example 3, I demonstrate this use-case asking Mistral-small to tell me how many deposits are shown in the bank statement. How to use Ensure your documents are either publicly accessible for Mistral-OCR or upload them to Mistral Cloud. Alternatively, signed urls from AWS S3 or Cloudflare R2 should also work. Requirements Mistral Cloud account and API Key. You'll also need credit on your account to use Mistral-OCR. Customising the workflow Mistral-OCR also works for images such as charts and diagrams so try using it on Financial Reports. Mistral-OCR is even cheaper with batching enabled. This returns your results within 24hrs but is half the price per page.

Overview This workflow allows you to trigger custom logic in n8n directly from Retell's Voice Agent using Custom Functions. It captures a POST webhook from Retell every time a Voice Agent reaches a Custom Function node. You can plug in any logic—call an external API, book a meeting, update a CRM, or even return a dynamic response back to the agent. Who is it for For builders using Retell who want to extend Voice Agent functionality with real-time custom workflows or AI-generated responses. Prerequisites Have a Retell AI Account A Retell agent with a Custom Function node in its conversation flow (see template below) Set your n8n webhook URL in the Custom Function configuration (see "How to use it" below) (Optional) Familiarity with Retell's Custom Function docs Start a conversation with the agent (text or voice) Retell Agent Example To get you started, we've prepared a Retell Agent ready to be imported, that includes the call to this template. Import the agent to your Retell workspace (top-right button on your agent's page) You will need to modify the function URL in order to call your own instance. This template is a simple hotel agent that calls the custom function to confirm a booking, passing basic formatted data. How it works Retell sends a webhook to n8n whenever a Custom Function is triggered during a call (or test chat). The webhook includes: Full call context (transcript, call ID, etc.) Parameters defined in the Retell function node You can process this data and return a response string back to the Voice Agent in real-time. How to use it Copy the webhook URL (e.g. https://your-instance.app.n8n.cloud/webhook/hotel-retell-template) Modify the Retell Custom Function webhook URL (see template description for screenshots) Edit the function Modify the URL Modify the logic in the Set node or replace it with your own custom flow Deploy and test: Retell will hit your n8n workflow during the conversation Extension Ideas Call a third-party API to fetch data (e.g. hotel availability, CRM records) Use an LLM node to generate dynamic responses Trigger a parallel automation (Slack message, calendar invite, etc.) 👉 Reach out to us if you're interested in analyzing your Retell Agent conversations.

Automate Amazon searches to Telegram with AI-powered scraping This workflow connects Amazon product lookups to Telegram using AI-enhanced scraping and automation. It lets users send a product name to a Telegram bot and instantly receive pricing, discount, and product links — all pulled dynamically from Amazon. Who’s it for Amazon affiliates Telegram shopping groups Product reviewers & resellers Deal-focused communities Anyone wanting fast price checks without browsing How it works Telegram Trigger receives messages from the user. AI Classifier (via OpenRouter & LangChain) detects whether the user is asking for a product. If yes, it sends the query to Apify's Amazon Scraper to fetch real product listings. The scraped data (price, discount, rating, link) is formatted into a Telegram response. If not a product query, an AI fallback response is sent instead. Requirements Telegram Bot Token Apify API Token OpenRouter API Key (or compatible LLM provider)

This n8n template automates the process of capturing leads from Webflow form submissions and syncing them with your Pipedrive CRM. It ensures that each submission is accurately associated with the correct organization and contact in Pipedrive, streamlining lead management and minimizing duplicates. Use cases include: Sales teams that want to automate CRM data entry, marketing teams capturing qualified leads from landing pages, or any business looking to improve their Webflow-to-CRM integration workflow. Good to know The workflow assumes that Webflow form submissions include the lead’s email address. The domain is extracted from the email to match or create the organization in Pipedrive. This template does not handle lead scoring or enrichment, but can be extended for such use-cases. How it works Extract website from email The email is split to extract the domain (e.g., jane@company.com → company.com), which is used to search for existing organizations. Check if the organization exists The Pipedrive API is queried using the domain. If the organization exists, we proceed. If not, a new organization is created. Check if the person exists -- If the person already exists in Pipedrive, a note is added to their activities to log the form submission. -- If the person does not exist, a new person is created, a note is added to the person, and a new lead is created. (Optional) Add your own actions You can extend this workflow to trigger Slack notifications, email follow-ups, or internal dashboards. How to use Start with the manual trigger node, or replace it with a webhook to connect directly to Webflow form submissions in real-time. Requirements Webflow form integration (via webhook or other method) Pipedrive account and API key Customising this workflow You can add enrichment services to auto-fill job titles or LinkedIn profiles. Perfect for growing sales pipelines without manual CRM input.

Use Case When building a product it's important to discover and eliminate bugs as quickly as possible. Since we're using our product at n8n a lot, we wanted to make it as easy as possible for everyone to add bugs with the needed level of detail. That's why we built this workflow that allows everyone to add bugs to our Linear account easily directly from Slack What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /bug command on a bot that you will create as part of this template. It then adds the bug to Linear using a pre-defined description and a defined label. It then notifies the user about the newly added bug as you can see below: How to create your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /bug as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Configure your Slack bot using the sticky to the left Fill the Set me up node. You can find the IDs easily using the Helper nodes section Make sure to exchange the Request URL in your Slack with the Prod URL of the Webhook node before activating this workflow How to adjust it to your needs Add zero, one, two or many labels when creating the new ticket Change the Slack message according to your needs Change the default description for a new bug ticket Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We're using AI to classify the bugs and move them to the right team as soon as they get added to Linear (see this template) We also added other commands like /pain and /idea that allow us to submit other things to Notion. You can see the workflow for that here.

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers a summary of the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts and summerizes them using AI to deliver a qucik overview for a busy sales rep. Delivers Insights**: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting and a summary of company's recent social media activity. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit OpenAI Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts Delivers Insight**s: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting, list of posts categorized by the social media platform, and direct links to posts. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

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