Workflow Templates

Extracting LinkedIn Profile Information Use Case Manually copying data from LinkedIn profiles is time-consuming and error-prone. This automation helps you extract structured, detailed information from any public LinkedIn profile—enabling fast enrichment, hiring research, or lead scoring. What This Automation Does This automation extracts profile details from a LinkedIn URL using the following input parameters: airtop_profile**: The name of your Airtop Profile connected to LinkedIn. linkedin_url**: The URL of the LinkedIn profile you want to extract data from. How It Works Starts with a form trigger or via another workflow. Assigns the LinkedIn URL and Airtop profile variables. Opens the LinkedIn profile in a real browser session using Airtop. Uses an AI prompt to extract structured information, including: Name, headline, location Current company and position About section, experience, and education history Skills, certifications, languages, connections, and recommendations Returns structured JSON ready for further use or storage. Setup Requirements Airtop API Key — free to generate. An Airtop Profile connected to LinkedIn (requires one-time login). Next Steps Sync with CRM**: Push extracted data into HubSpot, Salesforce, or Airtable for lead enrichment. Combine with Search Automation**: Use with a LinkedIn search scraper to process profiles in bulk. Adapt to Other Platforms**: Customize the prompt to extract structured data from GitHub, Twitter, or company sites. Read more about the Extract Linkedin Profile Information automation.

Automatically detect new n8n releases (stable or beta) from GitHub, update Coolify environment variables, and trigger deployments. Functionality This workflow automates deployment of n8n releases to a Coolify instance. It supports two tracks: Beta Releases: Checks GitHub every minute for prereleases, filters duplicates, updates the N8N_VERSION environment variable, and deploys. Stable Releases (disabled by default): Checks the latest stable release hourly and deploys. Key Features: Deduplication**: Ensures no repeated deployments for the same release. Version Parsing**: Extracts the semantic version (e.g., 1.34.0) from GitHub release names. Coolify Integration**: Updates environment variables and triggers deployments via API. Expected Outcomes New n8n beta/stable releases detected via GitHub API. Coolify environment variable N8N_VERSION updated to the latest version. Automatic deployment triggered in Coolify. Setup Guide Replace Placeholders: Update m8ccg8k44coogsk84swk8kgs in the Update ENV and Deploy nodes with your Coolify Application UUID. Configure Credentials: Add Coolify API credentials (httpHeaderAuth) with a valid API token in the headers. Enable Triggers: Toggle the Auto Update Latest Release node if stable releases are desired. Adjust schedule intervals as needed. Test: Run the workflow manually to validate API connections and version parsing. SEO Keywords Automated Deployment, n8n CI/CD, Coolify Integration, GitHub Release Monitoring, Environment Variable Management, Beta Release Automation.

⚠️ This Workflow Requires a Community Node and a Self-Hosted n8n Instance > This workflow uses the Vtiger CRM community node. To use it, you must be running a self-hosted version of n8n with Community Nodes enabled. 🔧 How to Install the Node Go to Settings → Community Nodes Click Install Node Enter the package name: n8n-nodes-vtiger-crm Restart your n8n instance if prompted 💬 Real-time Vtiger Support Tickets to Telegram with Auto Status Updates 📌 Overview Keep your support team instantly informed when new tickets are created in Vtiger CRM. This workflow: Fetches the most recent ticket marked as Open Sends its details to a Telegram chat Updates the status in Vtiger to In Progress to prevent re-sending 🔄 What This Workflow Does 📨 Pulls the latest open ticket from Vtiger HelpDesk 📲 Sends a rich-text message to Telegram with all key ticket details 🔁 Updates the ticket’s status to "In Progress" 🧠 Workflow Preview > 📲 Telegram Output Example > New ticket with the following details: Ticketid: TT2 Title: Internet down Status: Open Priority: High Severity: Minor Category: Small Problem Description: The internet was slow from yesterday and today is down completely 🛠️ Setup Instructions 🔗 Telegram Bot Setup Open Telegram and search for @BotFather Run /newbot and follow the instructions Save the bot token Add the bot to your chat or group Use @userinfobot to get your chat_id Paste the token and chat ID in the Telegram node inside n8n 🔗 Vtiger CRM Setup Make sure your Vtiger HelpDesk module includes: ticket_no, ticket_title, ticketstatus, ticketpriorities, ticketseverities, ticketcategories, description Connect your Vtiger API credentials inside n8n 👥 Who This Is For Customer support and IT helpdesk teams using Vtiger CRM Teams that want instant alerts in Telegram Anyone syncing CRM activity with chat-based notifications 🔐 Credentials Required ✅ Vtiger CRM API credentials ✅ Telegram Bot Token 🏷 Tags vtiger, telegram, crm automation, helpdesk alerts, no-code crm, realtime notifications, n8n telegram integration, support ticket automation, self-hosted n8n, community nodes, workflow automation, vtiger crm integration, helpdesk sync, n8n crm alerts `

Search music and play to Spotify from Telegram This workflow is a simple demonstration on accessing a message model from Telegram and it makes searching for songs an easy task even if you can't remember the artist or song name. An OpenAI message model tries to figure out the song and sends it to an active Spotify device**. Use case Imagine an office where you play music in the background and the employees can control the music without having to login to the playing account. How it works You describe the song in Telegram. Telegram bot sends the text to n8n. An OpenAI message model tries to find the song. Spotify gets the search query string. First match is then added to queue. -- If there is no match a message is sent to Telegram and the process ends. We change to the next track in the list. We make sure the song starts playing by trying to resume. We fetch the currently playing track. We return "now playing" information to Telegram: Song Name - Artist Name - Album Name. Error handling Every Spotify step has it's on error handler under settings where we output the error. Message parser receives the error and sends it to Telegram. Requirements Active workflow* OpenAI API key Telegram bot Spotify account and Oauth2 API Spotify active on a device** .* The Telegram trigger is activated only if this workflow is active. You can however TEST the workflow in the editor by clicking "Test step" and then it waits for the Telegram event. When event is received, just step through all steps or just clicking "Test step" on the "Fetch Now Playing" node. .** You must have a Spotify device active when trying to communicate with a device. Open Spotify and play something - not it is active.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🧠 Vtiger CRM – Auto-Answer FAQs with DeepSeek AI Description: This workflow automates the process of answering FAQ drafts in Vtiger CRM using DeepSeek LLM via LangChain. It's perfect for teams who want to accelerate knowledge base creation, improve support response consistency, or reduce the manual effort of writing FAQ content. Every 1 minute, this workflow: 📥 Retrieves the most recent FAQ record marked as Draft in Vtiger CRM 🧠 Sends the question to a LangChain agent powered by DeepSeek AI 📝 Receives a plain-text answer 📤 Updates the original FAQ with the generated answer and changes its status to Published ⚙️ How It Works Trigger:** Scheduled to run every 1 minute Query:** Pulls the latest FAQ from Vtiger where faqstatus = 'Draft' AI Agent:** Uses LangChain + DeepSeek to generate a natural-language answer Memory Buffer:** Keeps context using LangChain memory Update:** Pushes the answer back to Vtiger and marks it as Published 🛠️ Setup Instructions Connect Credentials for: Vtiger CRM API DeepSeek API Ensure your Vtiger CRM has a Faq module with fields: question faq_answer faqstatus Install the required Community Node: Go to Settings → Community Nodes Click Install Node and enter: n8n-nodes-vtiger-crm Restart your instance when prompted. Optionally customize the schedule or field names as needed. 👤 Who Is This For? Customer support teams building a knowledge base Businesses using Vtiger as a CRM or internal helpdesk Teams looking to automate repetitive content creation using LLMs 🔐 Credentials Required ✅ Vtiger CRM API credentials ✅ DeepSeek AI API key ✅ Highlights Fully automated LLM-powered FAQ generation Uses custom community node for Vtiger support Lightweight and runs on a short interval (1 min) Includes sticky note for clarity and onboarding Clean conditional logic and memory context built-in 🏷 Tags vtiger, crm, faq automation, ai automation, deepseek, langchain, llm, open source crm, faq generation, customer support, n8n, n8n community nodes, workflow automation, ai generated answers, vtiger integration, deepseek ai, langchain integration

Auto find & invite LinkedIn Leads This n8n template automates LinkedIn lead generation by scraping profiles, filtering out existing connections, and sending connection requests — all in a controlled, looped workflow. Ideal for outreach campaigns, recruitment, or lead gen efforts. ⚠️ Disclaimer – Community Node Notice This template uses a verified community node available inside the n8n cloud environment. To use it, go to "Nodes" → search for: Browserflow for Linkedin …and click Install. It’s officially verified and accessible directly from n8n cloud. In case you wish to run this template locally, you need to go to the settings, click community nodes and search for n8n-nodes-browserflow. Then after installing you can start using the actions in this node. 🛠️ How to Use Trigger: Manual Start Initiates the workflow manually via the “Test workflow” button, giving you full control. Scrape LinkedIn Profiles Uses the Browserflow automation to extract profile links from a LinkedIn search or keyword query. Split Out Results Converts the list of profiles into individual items for single-profile processing. Loop Through Each Profile Ensures each LinkedIn profile is handled one at a time, avoiding simultaneous actions. Check Existing Connection Verifies if you’re already connected with the lead on LinkedIn. Conditional Logic ✅ Already Connected → Skip to next profile ❌ Not Connected → Continue to next step Send Connection Invite Sends a LinkedIn connection request, optionally with a personalized message. 📦 Requirements n8n (cloud or self-hosted) Installed community node: Browserflow for Linkedin LinkedIn account Valid Browserflow acount (you can set up a free 7-day trial at https://browserflow.io) ⚙️ Setup Instructions Install the Browserflow Community Node Search “Browserflow for Linkedin” > Install. Get your API key Get your API key at https://browserflow.io Setup your Browserflow account After registering, setup your Browserflow and connect with Linkedin using the wizard at https://browserflow.io Connect with Browserflow by making a credential Click on the Browserflow actions to setup a connection with Browserflow by adding your API key to a credential. 🧩 Customization Tips Targeting: Adjust the Browserflow actions to scrape specific roles, industries, or locations. Messaging: You can add a message to the connection invite but remind that LinkedIn limits the amount of messages that can be send each month. Use variables in the message for personalization (e.g., {firstName}). Trigger: Replace manual trigger with a cron node for scheduled outreach. Integration: Combine with CRM tools (e.g., HubSpot, Notion, Airtable) for syncing leads or integrate with AI Agents.

Who is this for? This subworkflow is ideal for developers and automation builders working with UniPile and n8n to automate message enrichment and LinkedIn lead routing. What problem is this workflow solving? UniPile separates personal and organization accounts into two different API endpoints. This flow handles both intelligently so you're not missing sender context due to API quirks or bad assumptions. What this workflow does This subworkflow is used by: LinkedIn Auto Message Router with Request Detection** LinkedIn AI Response Generator with Slack Approval** It receives a message sender ID and tries to enrich it using UniPile's /people and /organizations endpoints. It returns a clean, consistent profile object regardless of which source was used. Setup Generate a UniPile API token and save it in your n8n credentials Make sure this subworkflow is triggered correctly by your parent flows Test both people and organization lookups to verify responses are normalized How to customize this workflow to your needs Add a secondary enrichment layer using tools like Clearbit or FullContact Customize the fallback logic or error handling Expand the returned data for more AI context or user routing (e.g., job title, region)

This n8n workflow template automates the process of collecting and delivering the "Top Deals of the Day" from MediaMarkt, tailored to user preferences. By combining user-submitted forms, Bright Data web scraping, GPT-4o-mini deal generation, and email delivery, this workflow sends personalized product recommendations straight to a user’s inbox. > ⚠️ Note: This workflow uses community nodes (Bright Data and Document Generator) which only work on *self-hosted n8n instances*. 🚀 What It Does Collects user preferences via a form (categories + email) Scrapes MediaMarkt’s deals page using Bright Data Uses GPT-4o-mini (OpenAI) to recommend top deals Generates a structured HTML email using a template Sends the personalized deals directly via email 🧩 Community Node Integration We created and used the following community nodes: Bright Data** – To scrape MediaMarkt deals using proxy-based scraping Document Generator** – To generate a templated HTML document from deal data These nodes are not available in n8n Cloud and require self-hosted n8n. 🛠️ Step-by-Step Setup Install Community Nodes Make sure you're on a self-hosted n8n instance. Install: n8n-nodes-brightdata n8n-nodes-document-generator Configure Credentials Bright Data API Key (Proxy + Scraping setup) OpenAI API Key (GPT-4o-mini access) SMTP Credentials for sending emails Customize the Form Adapt the form node to collect desired categories and email addresses. Typical categories include appliances, phones, laptops, etc. Design Your HTML Template In the Document Generator node, you can tweak the HTML/CSS to change how deals appear in the final email. Test the Workflow Submit the form with test data and check that the entire flow—from scraping to email—executes as expected. 🧠 How It Works: Workflow Overview User Interaction via Form Users select product categories and enter their email. This triggers the workflow. Data Extraction via Bright Data Bright Data scrapes the MediaMarkt offers page and returns HTML content. HTML Parsing Key elements like product names, prices, and links are extracted for processing. GPT-4o-mini Recommendation Generation The extracted data is sent to OpenAI (GPT-4o-mini), which filters, ranks, and enhances deals based on the user’s preferences. Data Structuring & Split The result is split into individual deal items to be formatted. HTML Document Creation Document Generator populates a clean HTML template with the top recommended deals. Email Delivery The final document is emailed via SMTP to the user with a friendly message. 📨 Final Output Users receive a custom HTML email featuring a curated list of top MediaMarkt deals based on their selected categories. 🔐 Credentials Used Bright Data API** – Web scraping with proxy support OpenAI API** – Generating personalized recommendations SMTP** – Sending personalized deal emails ✨ Customization Tips Change the Data Source**: You can adapt this to scrape other e-commerce sites. Update the Email Template**: Make it match your branding or include images. Extend the Form**: Add preferences like price range or specific brands. Add Scheduling**: Use Cron to run the workflow daily or weekly. ❓Questions? Template and node created by Miquel Colomer and n8nhackers.com. Need help customizing or deploying? Contact us for consulting and support.

AI-powered Telegram message analysis with multi-tool notifications (Gmail, Telegram) This workflow triggers on Telegram updates, analyzes messages with an AI Agent using MCP tools, and sends notifications via Gmail and Telegram. Detailed Description Who is this for? This template is for teams, businesses, or individuals using Telegram for communication who need automated, AI-driven insights and notifications. It’s ideal for customer support teams, project managers, or tech enthusiasts wanting to process Telegram messages intelligently and receive alerts via Gmail and Telegram. What problem is this workflow solving? Use case This workflow solves the challenge of manually monitoring Telegram messages by automating message analysis and notifications. For example, a support team can use it to analyze customer queries on Telegram with AI tools (OpenAI, Airbnb, Brave, FireCrawl) and get notified via Gmail and Telegram for quick responses. What this workflow does The workflow: Triggers on a Telegram update (e.g., a new message) using the Listen for Telegram Updates node. Processes the message with the Analyze Message with AI node, an AI Agent using MCP tools like OpenAI Chat, Airbnb search, Brave search, and FireCrawl. Sends notifications via the Send Gmail Notification and Send Telegram Alert nodes, including AI-generated insights. Setup Prerequisites: Telegram bot token for the trigger and notification nodes. Gmail API credentials for sending emails. API keys for OpenAI, Airbnb, Brave, and FireCrawl (used in the AI Agent). Steps: Configure the Listen for Telegram Updates node with your Telegram bot token. Set up the Analyze Message with AI node with your OpenAI API key and other tool credentials. Configure the Send Gmail Notification node with your Gmail credentials. Set up the Send Telegram Alert node with your Telegram bot token. Test by sending a Telegram message to trigger the workflow. Setup takes ~15-30 minutes. Detailed instructions are in sticky notes within the workflow. How to customize this workflow to your needs Add more AI tools (e.g., sentiment analysis) in the Analyze Message with AI node. Modify the notification message in the Send Gmail Notification and Send Telegram Alert nodes to include specific AI outputs. Add nodes for other channels like Slack or SMS after the AI Agent. Disclaimer This workflow uses Community nodes (e.g., Airbnb, Brave, FireCrawl), which are available only in self-hosted n8n instances. Ensure your n8n setup supports Community nodes before using this template.

Quickly transform any LinkedIn profile URL into a concise, AI‑generated professional summary — perfect for recruiters, sales teams, and hiring managers who need instant insights into prospects or candidates without manual research. How it works The workflow polls a Google Sheet for new or updated rows containing LinkedIn profile URLs. For each URL, the Real‑Time LinkedIn Scraper API (via RapidAPI) pulls experience and education sections. Extracted profile data is sent to OpenAI’s GPT model, which generates a clean, structured summary highlighting key strengths, career trajectory, and differentiators. The generated summary is written back into a new column in the same row of your Google Sheet for easy review and sharing. Set up steps Connect your Google account and select the spreadsheet + worksheet containing your list of LinkedIn URLs. Sign up for the Real‑Time LinkedIn Scraper API on RapidAPI, copy your API key, and add it to the workflow’s HTTP Request node. Insert your OpenAI API key credentials. Ensure your Google Sheet has one column for “linkedin_url” and create two empty columns named “full_name” and "summary" (or customize them based on your needs). Run a single row through the workflow to verify scraping accuracy and summary formatting, then turn on the workflow for continuous automation. With this template, eliminate hours of manual profile review — instantly gain actionable insights and focus on what really matters: building relationships and closing deals.

Overview This workflow retrieves all blog and event collection items from a Squarespace site and saves them into a Google Sheets spreadsheet. It uses pagination to fetch 20 items per request, ensuring all content is collected efficiently. How It Works The workflow queries your Squarespace blog and event collections. It fetches data in paginated batches (20 items per page). The retrieved data is formatted and inserted into Google Sheets. The workflow runs on demand or on a schedule, ensuring your data stays up to date. Requirements Credentials To use this template, you need: Your Squarespace collection URL Google Sheets API credentials Google Sheets Setup Use this sample Google Sheets template to get started quickly. Who Is This For? This template is designed for: Bloggers looking to manage and analyze content externally. Businesses and marketers tracking content performance. Anyone who needs an automated way to extract Squarespace blog and event data. Explore More Templates Check out my other n8n templates: 👉 n8n.io/creators/bangank36

This n8n training workflow demonstrates how to connect a sub-workflow as a tool to an AI Agent. In this example, the main workflow is a Website Chatbot that engages visitors, collects contact information, and sends that data to a CRM process. The CRM process itself is a separate sub-workflow, connected to the agent as a tool via the Tool Workflow node. Step-by-Step Setup Instructions 1. Create the Sub-Workflow (CRM Tool) This sub-workflow will be triggered by the AI agent to process collected information. It will: Receive inputs (email, description) from the main chatbot workflow. Format the data into a structured JSON format. Append the data to a Google Sheet (acting as the CRM database). Send a confirmation message back to the main workflow. Steps inside the sub-workflow: When Executed by Another Workflow** – Triggered by the main workflow’s tool node. Convert Conversation (Agent)** – Uses OpenAI to extract and format the input into a JSON structure: { "email": "jane.doe@example.com", "description": "Wants help automating lead intake and sending Slack notifications." } Structured Output Parser – Ensures the extracted data matches the expected JSON schema. Append row in sheet (Google Sheets) – Adds the new lead data to your CRM sheet. Code Node – Returns a simple text confirmation like "Thanks for the info, we will be in touch soon". Required setup for Google Sheets: Enable the Google Sheets API and connect your Google account in n8n. Create a sheet with at least the columns email and description. Use the sheet's Document ID and tab name in the Google Sheets node. 2. Create the Main Workflow (Website Chatbot) This workflow acts as the main AI Agent handling incoming chat messages. Steps in the main workflow: When chat message received – Starts the workflow whenever a visitor sends a message via your chatbot integration. Website Chatbot (Agent Node) – Configured with a System Message that: Briefly explains your services. Asks the visitor what processes they want to automate. Requests their name and email. Sends collected data to the CRM tool once email and description are available. OpenAI Chat Model – Connects to the AI agent as its language model. Simple Memory – Stores short-term context for the ongoing chat. CRM Tool (Tool Workflow Node) – Points to the sub-workflow created in Step 1, allowing the chatbot to trigger it directly. 3. Connecting the Sub-Workflow to the AI Agent Add a Tool Workflow node to the main workflow. Select "Parameter" as the source. Paste in your sub-workflow JSON or select it from your n8n workflows. Connect the Tool Workflow node to your AI Agent using the ai_tool connection. Give the tool a clear description (e.g., crm tool to store lead information) so the agent knows when to use it. 4. How It Works in Action A visitor sends a message through the chatbot. The AI Agent engages, asks questions, and collects their name, email, and request. Once collected, the agent triggers the CRM Tool. The sub-workflow formats the data, stores it in Google Sheets, and sends a confirmation. The chatbot confirms with the visitor that their request was received. 5. Customization Ideas Replace Google Sheets with your actual CRM API. Add validation to ensure the email format is correct before saving. Expand the CRM tool to send a Slack or email notification after storing the lead. Created by Robert A. – Ynteractive Website: https://ynteractive.com Email: robert@ynteractive.com