Workflow Templates

Description This n8n workflow enables users to send an image to a Telegram bot and receive the extracted text using Tesseract OCR (via the n8n-nodes-tesseractjs Community Node). It's a quick and straightforward way to convert images into readable text directly through chat. How it Works The workflow listens for new image messages coming in via the Telegram bot. Once an image is received, it downloads the image file from Telegram (which initially arrives as application/octet-stream). The image data, now properly identified, is then sent to the Tesseract OCR node to extract the text. Finally, the recognized text is sent back as a reply to the Telegram user. Setup Steps Install Community Node: Ensure you have installed n8n-nodes-tesseractjs in your n8n instance. Connect Telegram Bot: Configure the Telegram Trigger node with your Telegram bot. Bot Token: Add your Telegram bot token to the Send Message node to send replies. Deploy & Test: Activate (deploy) the workflow and send an image to your Telegram bot to test.

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.

This n8n template demonstrates how to use AI as a comprehensive personal assistant with multiple specialized agents. Use cases include email management, scheduling, web search, calculations, and more - all automated through AI coordination. Good to know This template integrates multiple AI services through OpenRouter Each agent specializes in different tasks (Gmail, Calendar, Search, etc.) Memory persistence maintains context across interactions How it works The workflow is triggered by Telegram messages (can be replaced with other triggers) A router node directs requests to the appropriate specialized agent Agents include: Gmail for email management Calculator for math operations Google Search for information retrieval Calendar for scheduling Contacts for CRM functions The OpenRouter Chat Model coordinates responses Final responses are sent back through Telegram How to use Connect your Telegram bot credentials Configure each service with appropriate API keys The system will automatically route requests to the right agent Requirements OpenRouter account for AI services Telegram bot token Google API credentials for relevant services Customising this workflow Add more specialized agents as needed Replace Telegram with other communication channels Adjust routing logic for different use cases

This workflow converts Notion pages to markdown, and then converts that markdown back to Notion blocks. It will triple the content of the last updated page it finds. This is useless by itself, but you can copy-paste from this workflow to create your own. Prerequisites A notion account with some pages or databases Setup instructions Create a notion credential and share some pages as described here: https://docs.n8n.io/integrations/builtin/credentials/notion/ How it works The HTTP Request gets notion child blocks from a page, because the default n8n block only gets plain text and no links. The first code block converts it to markdown. The second code block converts it back to Notion blocks The last HTTP block appends everything to the original Notion page, essentially duplicating it for the purpose of demoing the script. I hope in the future we get official n8n blocks that extract markdown, or use markdown to write to Notion. There is community block that also does this, but this template is easier: you can simply copy-paste the blocks from this workflow.

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.

Automating LinkedIn Profile Discovery with Verification Use Case Accurately identifying and verifying a person’s LinkedIn profile is essential for prospecting, recruiting, or contact enrichment. This automation ensures high accuracy by combining search logic with optional profile validation. What This Automation Does This automation locates and verifies a LinkedIn profile using the following inputs: Person_info**: Any identifying information about the person (e.g., name, company, email). Airtop_profile**: Your Airtop Profile authenticated on LinkedIn, used for verifying the profile. How It Works Extracts a likely LinkedIn URL by performing a Google search using the provided person info. Validates the result (if Airtop Profile is provided): Visits the LinkedIn profile. Verifies match by checking the content (e.g., experience, role) against the person info. Returns a verified LinkedIn profile URL or "NA" if not found or not valid. Setup Requirements Airtop API Key Optional but recommended: an Airtop Profile authenticated on LinkedIn. Next Steps Combine with Email Lookup**: Use email-to-profile tools upstream to gather inputs. CRM Integration**: Automatically append LinkedIn profiles to contact records. Automate Outreach**: Use the verified URLs for personalized LinkedIn engagement workflows. Read more about how find and verify Linkedin profiles

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

Auto-Categorize Outlook Emails with AI in n8n How It Works Trigger: The workflow starts with the Microsoft Outlook Trigger node, polling your inbox every minute for new emails. Extract & Clean Email Content: The email’s key fields (from, subject, isRead, body) are extracted. The body is converted from HTML to Markdown, then sanitized to plain text for reliable AI processing. Node Setup Details: Microsoft Outlook Trigger Resource: Message Operation: Trigger on new email Fields to Output: from, subject, isRead(optional), body Folders to Include: (Set to your Inbox or specific folder IDs) Markdown Node Input: {{$json"body"}} (HTML email body) Output Key: Email Body Markdown Purpose: Converts HTML to Markdown for easier downstream processing. Sanitize Node (Code Node) Input: Email Body Markdown from previous node Purpose: Cleans up Markdown, strips images, links, HTML tags, table formatting, and truncates to 4000 characters. Sample JS Code: // Get the markdown content from the previous node const markdownContent = $input.item.json["Email Body Markdown"]; Setup AI tools Move message and Get Folders Outlook tools are required, get contacts is optional. Set each field in the tools to "defined automatically by the model" and describe each field so the model understands how to use it. OpenRouter or other LLM models tool: You can use any client for this, but make sure to use a model that does well with tool calls (Claude, GPT-4.1, Gemini 2.5 Pro, etc.). Best Practices & Notes AI Prompt Engineering:** The AI is instructed to be conservative—never move emails from real people or saved contacts, and always explain its reasoning if it doesn’t move a message. This automation only works for NEW incoming messages. Inbox Zero:** This system is designed to help you achieve and maintain Inbox Zero by keeping only actionable items in your main inbox. Customization:** You can adjust the folder logic, add more categories, or tweak the AI prompt for your specific needs. Privacy:** All processing happens within your n8n instance; no email data is stored outside your environment except for the AI call (which only receives sanitized, minimal content).

n8n Workflow: OpenAI DALL·E 2 Image Generation & Google Drive Upload Description This n8n workflow automates the process of generating multiple AI-created images from a single prompt using OpenAI's DALL·E 2, then uploads the results directly to a Google Drive folder. It includes a loop to produce several image variations for the same prompt, making it ideal for creative projects, marketing materials, or content experimentation. Step-by-Step Setup Instructions 1. Prepare Your API Keys OpenAI API Key** Sign up or log in at https://platform.openai.com/ Go to API Keys and create a new one. Copy and store this securely — you'll need it in n8n. Google Drive API** Go to https://console.cloud.google.com/ Create a project and enable Google Drive API. Create OAuth 2.0 credentials and set the redirect URI to your n8n OAuth redirect (found in your n8n Google Drive node setup). Connect your Google account when adding credentials in n8n. 2. Workflow Nodes Overview Manual Trigger – Starts the workflow manually. Set Image Prompt – Stores the prompt text and base file name (e.g., “Make an image of an attractive woman standing in New York City”). Duplicate Rows (Code Node) – Creates multiple "runs" of the same prompt for variation. Loop Over Items – Processes each variation one at a time. Generate an image (OpenAI DALL·E 2) – Sends the prompt to OpenAI and retrieves an image. Upload to Google Drive – Saves each generated image to your chosen Google Drive folder. 3. Building the Workflow in n8n Step 1 — Manual Trigger Add a Manual Trigger node to start the workflow manually when testing. Step 2 — Set Image Prompt Add a Set node with two fields: Prompt → The image description text. Name → The base name for the saved file. Example: | Name | Value | |--------|---------------------------------------------------------------| | Prompt | Make an image of an attractive woman standing in New York City | | Name | woman-nyc | Step 3 — Duplicate Rows (Code Node) Use this JavaScript to create three copies of the prompt (run 1, run 2, run 3): const original = items[0].json; return [ { json: { ...original, run: 1 } }, { json: { ...original, run: 2 } }, { json: { ...original, run: 3 } }, ]; Step 4 — Loop Over Items Insert a Split in Batches node and set the batch size to 1. This ensures each prompt variation runs through the image generation process individually. Connect this node so it runs after the Duplicate Rows node. Step 5 — Generate Image Add the OpenAI Image Generation node and configure it as follows: Model**: dall-e-2 Prompt**: ={{ $json.Prompt }} Leave other options at their defaults unless you want to specify image size or style. Connect your OpenAI API credentials created in Step 1. This node will send the current prompt in the batch to OpenAI's DALL·E 2 model and return an AI-generated image. Step 6 — Upload to Google Drive Add a Google Drive node and configure it to store the generated image: File Name**: ={{ $('Set Image Prompt').item.json.Name }} - {{ $('Duplicate Rows').item.json.run }} Folder ID**: Select the target Google Drive folder where images should be saved. Connect your Google Drive OAuth2 API credentials. The node will upload each generated image to your chosen Google Drive location, with a unique filename for each variation. Running the Workflow Execute the workflow manually. The process will: Loop through each prompt variation. Generate an image using OpenAI DALL·E 2. Upload the image to Google Drive with a unique name. You will find all generated images in the selected Google Drive folder. Customization Tips Change the number of variations by editing the Duplicate Rows code. Adjust the prompt dynamically from other data sources like Google Sheets, webhooks, or forms. Schedule the workflow to run at specific times or trigger it via an API call. Created by Robert A. – Ynteractive Website: https://ynteractive.com Email: robert@ynteractive.com

This n8n template from Intuz provides a complete and automated solution for hyper-personalized email outreach. It powerfully combines AI with Gmail and Google Sheets, using specific keywords and prospect data to automatically craft unique, compelling email content that boosts engagement and secures more replies. Instead of manually replying to every lead or inquiry, this template does the heavy lifting for you, ensuring every response is relevant, thoughtful, and timely. It reads each person's unique inquiry, uses OpenAI to craft a perfectly tailored and human-like response, and sends it directly from your Gmail account. Ideal for sales, marketing, and customer support teams looking to boost engagement and save hours of manual work. Use Cases: Sales Teams: Instantly follow up with new leads from your website's contact form with a personalized touch. Customer Support: Provide initial, intelligent responses to support tickets, answering common questions or acknowledging receipt of a complex issue. Marketing Automation: Nurture leads by responding to content downloads or webinar sign-ups with relevant, non-generic information. Founders & Solopreneurs: Manage all incoming business inquiries (partnerships, media, etc.) efficiently without sacrificing quality. How It Works: Trigger the Flow (Manual): Start the automation whenever you're ready to process a new batch of inquiries from your sheet. Fetch Inquiries from Google Sheets: The workflow connects to your specified Google Sheet and reads each row. It pulls the contact's First Name, Email ID, the Inquiry Intent (e.g., "Demo Request," "Pricing Inquiry"), and the full text of their Original Inquiry. Sync Your Signature: Before writing the email, an HTTP Request node dynamically fetches your display name from your Gmail account settings. This ensures the signature in the generated email (Thanks, {{Your Name}}) is always accurate. Craft a Hyper-Personalized Reply with AI: It uses this context to generate a high-quality, professional, and friendly email reply in HTML format. For example: If the intent is "Technical Support," the AI will generate a helpful, empathetic response addressing the technical issue. If the intent is "Partnership Proposal," it will draft a professional reply acknowledging the proposal and outlining the next steps. Send via Gmail: The final node takes the AI-generated message, adds a relevant subject line (e.g., "Re: Your Demo Request"), and sends it directly to the contact's email address from your connected Gmail account. This process loops for every single row in your Google Sheet, turning a list of names into a series of meaningful conversations. Setup Instructions: To get this workflow running, you'll need to configure a few things: Credentials: Google: Connect your Google account via OAuth2 and ensure you have enabled access for Google Sheets, Google Drive, and Gmail. OpenAI: Add your OpenAI API key as a credential. Google Sheet Setup: Create a Google Sheet with the following exact column headers: -First Name -Email ID -Inquiry Intent (A short category like "Demo Request", "Billing Issue", etc.) -Original Inquiry (The full text of the email or message you received). Node Configuration: Get row(s) in sheet: Select your Google Sheet document and the specific sheet name. Message a model (OpenAI): Choose your preferred OpenAI model (e.g., gpt-4-turbo, gpt-3.5-turbo). HTTP Request & Send Personalized emails: These nodes should automatically use your configured Gmail credentials. No changes are typically needed. Connect with us Website: https://www.intuz.com/cloud/stack/n8n Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz

Automated pipeline that extracts job listings from Upwork and exports them to Google Sheets for better organization, analysis, and team collaboration. 🚀 What It Does Fetches job postings based on saved searches Extracts key job details (title, budget, description) Organizes data in Google Sheets Updates in real-time Supports multiple search criteria 🎯 Perfect For Freelancers tracking opportunities Teams managing multiple projects Agencies monitoring client needs Market researchers Business analysts ⚙️ Key Benefits ✅ Centralized job board ✅ Easy sharing with team members ✅ Advanced filtering and sorting ✅ Historical data tracking ✅ Customizable data points 🔧 What You Need Upwork account Google account n8n instance Google Sheets setup 📊 Data Exported Job title and description Budget and hourly rate Client information Posted date Required skills Job URL 🛠️ Setup & Support Quick Setup Get started in 15 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Streamline your job search and opportunity tracking with automated data collection and organization.

How it works creates a new page in Confluence based on a page template also defined in Confluence replaces any number of placeholders with data from your workflow generic implementation for maximum flexibility Set up steps All parameters you need to change are defined in the Set node Set your Atlassian-domain Set the template id you want to use as the basis for new pages Set the target space and parent page for new pages added based on that template. 🎥 Explainer video has all the details. =) Feedback Any feedback is welcome. If you have ideas for improvements, let me know.