by Hugues Stock
What does this template do ? This workflow performs scheduled health checks on a list of URLs stored in a Google Sheet. Every X minutes, it retrieves the URLs, sends HTTP requests to check their availability, and notifies a Telegram chat if any request fails. You can easily replace Telegram with any other notification service supported by n8n, such as Slack, Discord, Email, or Microsoft Teams. Use Case Ideal for monitoring internal or external services, ensuring uptime and responsiveness. Integrate with your preferred messaging platform for real-time failure notifications—without setting up complex infrastructure. What the Workflow Does ⏰ Triggers at regular intervals using Schedule Trigger 📄 Reads URLs from a Google Sheet 🌐 Sends HTTP requests to check URL health 🚨 Sends failure alerts (including error code and URL) to Telegram (or any service of your choice) Apps & Services Used Google Sheets Telegram (or alternative notification service) HTTP Request Pre-requisites Telegram bot and chat ID (if using Telegram) Connected Google Sheet with a URLS column (template) Customization Tips Adjust the schedule interval in the trigger node Replace Telegram with Slack, Email, Discord, or any other notification node Customize alert messages with more context or formatting Add filters, retries, or logging as needed
by Vishal Kumar
Problem Teams often struggle with email overload, leading to missed actions and inefficient meeting preparation. Solution This workflow automates email management using n8n and AI. It fetches emails, summarizes key points and actions, and sends two concise updates—one in the morning and one at night. How It Works Triggers at 7 AM and 9 PM: Automates the process to summarize emails received during specific time blocks. Fetches Emails: Retrieves emails from the last 24 hours or after a specific time. Summarizes with AI: Uses OpenAI to process the email content into actionable summaries. Sends Team Updates: Compiles the summaries into a concise, formatted email and sends it to the team. Expected Results Significant reduction in missed actions and follow-ups. Customizations Adjust timings, filters, and recipients to suit your team’s needs.
by AmirHossein MnasouriZade
📦 Send Telegram Notifications for New WooCommerce Orders This workflow automatically sends a Telegram notification when an order status in WooCommerce changes to "Processing." Perfect for online store owners who want instant updates on order fulfillment. ⚙️ Set Up Telegram Alerts for WooCommerce Orders Configure WooCommerce Webhook to trigger on order updates. Create a Telegram Bot and obtain the API token. Set Up Telegram Credentials in n8n. Configure the Telegram Node with your chat ID. Activate and Test the workflow by placing a new order. ##💡 Notes You can customize the message format in the 🖋️ Design Message Template node to include additional order details. Contact me on [Telegram]: https://t.me/amir676080 Message structure includes the following details 🆔 Order Number: 11234 👦🏻 Customer Name: John Doe 💵 Amount: 299.99 USD 📅 Order Date: ➖ 25th November 2024 at 14:42 🏙 City: New York 📞 Phone: +1 555-1234 ✍🏻 Order Note: Fast delivery requested 📦 Ordered Products: 🔹 Wireless Earbuds (2 items) 📝 Type: Premium Sound Edition Contact me on [Telegram]: https://t.me/amir676080
by Airtop
About the Automation Staying on top of competitor pricing changes can be a full-time job. Manual price tracking is time-consuming and prone to errors, especially when dealing with complex pricing structures and multiple subscription tiers. Paid competitor price monitoring tools like Competera, Visualping and Fluxguard can be expensive. What if you could automate this process and get instant alerts when competitors adjust their pricing? How to easily monitor competitor pricing With this automation, you'll learn how to set up automated price monitoring system using Airtop's built-in node in n8n. By the end, your system will automatically track competitor pricing changes and notify you of any modifications. What You'll Need A free Airtop API Key Google Sheets account with a copy of this sheet URLs of competitors' pricing pages Understanding the Process This automation continuously monitors competitor pricing pages and compares them against your baseline data. The workflow: Tracks all different pricing plans (monthly, yearly, etc.). Monitors feature changes across different tiers. Detects and logs pricing structure modifications. Alerts you via Slack when changes are detected Setting Up Your Automation We've created a ready-to-use blueprint for seamless price monitoring. Here's how to get started: Connect your Google Sheets Set up your Airtop API connection Define update frequency Customization Options Enhance the basic template with these popular modifications: Add other notification channels (Email, Telegram, etc.). Include feature comparison tracking. Set up threshold-based alerts for significant price changes Track historical pricing trends Real-World Applications Case Study 1: A B2B SaaS company can use this automation to track competitors' pricing changes. When they identify a market-wide pricing shift, they can adjust their strategy proactively within minutes. Case Study 2: An online Ecommerce retailer automates monitoring of 100+ competitor products, maintaining optimal pricing positions and increasing profit margins. Best Practices To ensure accurate tracking: Include detailed baseline data for each pricing tier Specify both monthly and annual pricing clearly List all features included in each plan Update your baseline data whenever you verify changes Include any promotional pricing or special offers Document currency and regional variations if applicable Example Structure in Google Sheets: Competitor: Acme Tools Basic Plan: Monthly: $29 Annual: $290 ($24.17/mo) Features: 5 users, 10GB storage, basic support Pro Plan: Monthly: $79 Annual: $790 ($65.83/mo) Features: 20 users, 50GB storage, priority support What's Next? After setting up your price monitoring automation, consider the following: Creating automated competitive analysis reports Setting up market trend analysis Implementing automatic pricing recommendations Expanding monitoring to feature changes Happy monitoring!
by Samir Saci
Tags: Sustainability, CSRD, Reporting, ESG, Compliance, Automation Context Hey! I'm Samir, a Supply Chain Engineer and Data Scientist from Paris, founder of LogiGreen Consulting We help companies automate sustainability workflows using AI, Data Analytics, and No-Code tools like N8N. > Sustainability Reporting meets Automation with n8n! 📬 For business inquiries, you can add me on Here What is a CSRD XHTML Report? Under the Corporate Sustainability Reporting Directive (CSRD), companies must publish their ESG disclosures in a machine-readable XHTML format, embedding XBRL tags that make the report structured and standardized. These files must follow strict formatting and tagging rules to ensure compliance, traceability, and accessibility for both regulators and analysts. Who is this template for? This workflow is designed for sustainability teams, ESG consultants, or developers who want to automatically check the structure and format of CSRD reports submitted in XHTML. How does it work? This N8N workflow automates the audit process: 📤 Input Node → Uploads or fetches the XHTML file via URL or Webhook. 🧪 Validates Structure → Uses a custom code node to parse HTML and identify required tags (e.g., <ix:nonNumeric>, namespaces). 📋 Outputs a Report → Returns a summary report of errors, warnings, and key metadata (like entity name, reporting period). 📤 Export Option → Save the results in Google Sheets or send via email. Prerequisite A sample XHTML file that you can find in my GitHub Repository Google Sheets API* and *OpenAI API** credentials Next Steps Follow the sticky notes inside each node to adjust parsing rules or extend validation to specific XBRL tags relevant to your sector (e.g., GHG emissions, water usage). *📺 Check my complete tutorial to understand how to use it: * 🎥 Check My Tutorial 🚀 Interested in combining CSRD compliance with automation and analytics? Let’s connect on LinkedIn Notes This workflow includes an example XHTML file to test the validator. You can plug this into your internal systems or even extend it with AI to auto-summarize the sustainability report. This workflow has been created with N8N 1.82.1 Submitted: April 3rd, 2025
by Jonathan
This workflow searches for mentions of a company's name on Twitter and shares the tweets that mention it in a Slack channel. Prerequisites A Slack account and credentials A Twitter account and credentials Nodes Cron node executes the workflow every 10 minutes. Note that if you change the Mode from "Every X" you will need to manually update the Date & Time node to subtract the interval you are using. Set nodes set the required values (name of the Slack channel, name of the Twitter account to search for, the tweet text and URL). Date & Time node subtracts 10 minutes from the workflow execution time. Twitter node gets the latest 50 tweets that mention the specified account. IF node filters tweets posted in the past 10 minutes. Slack node posts tweets in a Slack channel.
by Omer Fayyaz
An intelligent AI-powered agent that automatically browses publication websites, analyzes page content with natural language understanding, and identifies the latest downloadable reports, research papers, and data files across multiple sources using advanced structured output parsing. What Makes This Different: AI-Powered Content Analysis** - Uses advanced language models (GPT-4/GPT-5.1) to understand page context and identify downloadable reports, even when links aren't explicitly labeled, handling complex page layouts and dynamic content Structured Output Parsing** - Enforces JSON schema validation ensuring consistent data extraction with required fields (title, link, file_type, description), eliminating parsing errors and data inconsistencies HTML to Markdown Conversion** - Converts raw HTML to clean Markdown before AI processing, removing noise and improving AI comprehension of page structure and content hierarchy Intelligent Link Detection** - AI agent identifies direct download URLs, converts relative links to absolute URLs, and prioritizes the most recent reports based on publication dates and page positioning Comprehensive Validation** - Multi-layer validation checks link format, file type detection, and report relevance before saving, ensuring only valid, downloadable reports enter your library Flexible Source Management** - Reads publication sources from Google Sheets, enabling easy addition/removal of sources without workflow modification, with support for categories and custom metadata Key Benefits of AI-Powered Report Discovery: Automated Discovery** - Eliminates manual browsing and searching across multiple publication sites, saving hours of research time while ensuring you never miss new reports Context-Aware Extraction** - AI understands page context, distinguishing between actual reports and navigation links, category pages, or promotional content Prioritized Results** - Automatically selects the most recent and relevant report from each source, focusing on quality over quantity Structured Data Output** - All discovered reports are saved with consistent metadata (title, link, file type, description, source), making them easy to search, filter, and integrate with other systems Error Resilience** - Handles missing reports gracefully, logging when no reports are found without failing the entire workflow, ensuring continuous operation Integration Ready** - Can be called by other workflows (e.g., PDF downloader), enabling end-to-end automation from discovery to storage Who's it for This template is designed for researchers, market analysts, competitive intelligence teams, academic institutions, industry monitoring services, and anyone who needs to systematically discover and track downloadable reports from multiple publication sources. It's perfect for organizations that need to monitor industry publications, track competitor research, discover new market reports, build research libraries, or stay updated on latest publications without manually visiting dozens of websites daily. How it works / What it does This workflow creates an AI-powered report discovery system that reads publication source URLs from Google Sheets, fetches their pages, uses AI to analyze content, and extracts information about downloadable reports. The system: Reads Active Sources - Fetches publication URLs and metadata from Google Sheets "Report Sources" sheet, processing each source in sequence Loops Through Sources - Processes sources one at a time using Split in Batches, ensuring proper error isolation and preventing batch failures Fetches Publication Pages - Downloads HTML content from each source URL with proper browser headers (User-Agent, Accept, Accept-Language) to avoid blocking Converts HTML to Markdown - Transforms raw HTML into clean Markdown format, removing styling, scripts, and navigation elements to improve AI comprehension AI Analysis - LangChain agent analyzes the Markdown content using GPT-4/GPT-5.1, identifying downloadable reports based on context, link patterns, and content structure Structured Output Parsing - Enforces JSON schema validation, ensuring the AI returns data in the exact format: source, title, link, file_type, description Validates & Normalizes Output - Validates extracted links are absolute URLs, checks file type indicators, determines report validity, and normalizes all fields Routes by Validity - IF node routes valid reports to save operation, invalid/missing reports to logging Saves Discovered Reports - Appends valid reports to Google Sheets "Discovered Reports" sheet with metadata, source URL, category, and discovery timestamp Logs No Report Found - Records sources where no valid reports were found in "Discovery Log" sheet for monitoring and troubleshooting Tracks Completion - Generates completion summary with number of sources checked and processing timestamp Key Innovation: AI-Powered Context Understanding - Unlike traditional web scrapers that rely on fixed CSS selectors or regex patterns, this workflow uses AI to understand page context and semantics. The AI can identify reports even when they're embedded in complex layouts, use non-standard naming, or require understanding of surrounding text to determine relevance. This makes it adaptable to any website structure without manual configuration. How to set up 1. Prepare Google Sheets Create a Google Sheet with three tabs: "Report Sources", "Discovered Reports", and "Discovery Log" In "Report Sources" sheet, create columns: Source_Name, Source_URL, Category (optional) Add publication URLs in the Source_URL column (e.g., "https://example.com/research" or "https://publisher.com/reports") Add descriptive names in Source_Name column for easy identification Optionally add Category values (e.g., "Market Research", "Industry Reports", "Academic Papers") The "Discovered Reports" sheet will be automatically populated with columns: source, title, link, fileType, description, sourceUrl, category, discoveredAt, status, isValid The "Discovery Log" sheet will record sources where no reports were found Verify your Google Sheets credentials are set up in n8n (OAuth2 recommended) 2. Configure Google Sheets Nodes Open the "Read Active Sources" node and select your spreadsheet from the document dropdown Set sheet name to "Report Sources" Configure the "Save Discovered Report" node: select same spreadsheet, set sheet name to "Discovered Reports", operation should be "Append or Update" Configure the "Log No Report Found" node: same spreadsheet, "Discovery Log" sheet, operation "Append or Update" Test connection by running the "Read Active Sources" node manually to verify it can access your sheet 3. Set Up OpenAI Credentials Open the "OpenAI GPT-5.1" node (or configure the model you want to use) Connect your OpenAI API credentials (API key required) The workflow uses GPT-5.1 by default, but you can change to GPT-4, GPT-4 Turbo, or other models Temperature is set to 0.1 for consistent, deterministic output Verify API key has sufficient credits and access to the selected model For cost optimization, GPT-4 Turbo is recommended for similar results at lower cost 4. Configure AI Agent & Output Parser The "AI Report Discovery Agent" node contains a detailed system prompt that instructs the AI on what to look for The prompt is pre-configured but can be customized for your specific needs (e.g., prioritize certain file types, look for specific keywords) The "Structured Output Parser" enforces the JSON schema - verify the schema matches your needs: { "source": "Publisher Name", "title": "Report Title", "link": "https://example.com/report.pdf", "file_type": "pdf", "description": "Brief description" } The parser ensures the AI always returns valid JSON with all required fields Test the AI agent by manually running with a sample source URL to verify it correctly identifies reports 5. Customize Discovery Rules (Optional) The AI agent's system prompt can be modified in the "AI Report Discovery Agent" node Current rules prioritize: downloadable files (PDF, Excel, Word, PowerPoint), most recent publications, direct download URLs To customize: Edit the system message to add specific keywords, file types, or discovery patterns Example customization: Add industry-specific terms or prioritize reports with certain keywords in titles The validation code in "Validate & Normalize Output" can be adjusted to change what's considered "valid" Test with your specific sources to ensure discovery rules work as expected 6. Set Up Scheduling & Test The workflow includes Manual Trigger (for testing), Schedule Trigger (runs daily), and Execute Workflow Trigger (for calling from other workflows) To customize schedule: Open "Schedule (Daily)" node and adjust interval (e.g., twice daily, weekly) For initial testing: Use Manual Trigger, add 2-3 test publication URLs to your "Report Sources" sheet Verify execution: Check that pages are fetched, AI analysis completes, and reports are saved to "Discovered Reports" Monitor execution logs: Check for API errors, timeout issues, or parsing failures Review Discovery Log: Verify sources with no reports are properly logged Common issues: OpenAI API rate limits (add delays if processing many sources), invalid URLs (check source URLs), timeout errors (increase timeout for slow-loading pages), AI not finding reports (may need to adjust system prompt for specific site structures) Requirements OpenAI API Key** - Active OpenAI account with API access and sufficient credits for GPT-4/GPT-5.1 model usage (API key configured in n8n credentials) Google Sheets Account** - Active Google account with OAuth2 credentials configured in n8n for reading and writing spreadsheet data Source Spreadsheet** - Google Sheet with "Report Sources", "Discovered Reports", and "Discovery Log" tabs, properly formatted with required columns Valid Publication URLs** - Direct links to publication pages that contain downloadable reports (not direct PDF links - the workflow discovers those) n8n Instance** - Self-hosted or cloud n8n instance with access to external websites (HTTP Request node needs internet connectivity) and LangChain nodes enabled
by Lorena
This workflow collects images from web search results on a specific query, analyzes the image for labels, formats the text, and adds the information in Google Sheets. HTTP Request node** gets images from the web. AWS Rekognition node** analyzes the images (in this case, it detects text in an image). Set node** sets the values necessary for the data set. Function node** transforms the text detected in the image to lower case. Google Sheets node** adds the image information to a sheet that serves as data set.
by Harshil Agrawal
This workflow allows you to add positive feedback messages to a table in Notion. Prerequisites Create a Typeform that contains Long Text filed question type to accepts feedback from users. Get your Typeform credentials by following the steps mentioned in the documentation. Follow the steps mentioned in the documentation to create credentials for Google Cloud Natural Language. Create a page on Notion similar to this page. Create credentials for the Notion node by following the steps in the documentation. Follow the steps mentioned in the documentation to create credentials for Slack. Follow the steps mentioned in the documentation to create credentials for Trello. Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form. Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score. IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is positive (larger than 0). If the score is positive we get the result as True, otherwise False. Notion node: This node gets connected to the true branch of the IF node. It adds the positive feedback shared by the user in a table in Notion. Slack node: This node will share the positive feedback along with the score and username to a channel in Slack. Trello node: If the score is negative, the Trello node is executed. This node will create a card on Trello with the feedback from the user.
by Lucas Perret
This workflow will allow you to enrich in real-time a form submission from Webflow using Datagma. Based on the result of this workflow, a specific Calendly link will be shown on the website. If the process outcome is '1', a link for a one-on-one demo will be provided. If the process outcome is '2', a link for a group demo will be shown. Full guide here: Real-time Lead Routing
by kreonovo
What this does: This automation will dynamically create channels on your Discord server for each of your Webflow forms then send formatted form submissions as messages in those channels. This is useful for Webflow will only notify a single email of a form submission. By using this workflow you can enhance your Webflow form management by receiving them in Discord. This is great if you need to notify multiple team members or communities of your form submissions. Usage guide Full written and video guide Simply create credentials for Webflow and Discord and connect them to the nodes. The video guide demonstrates a realworld usecase using a Webflow template and breaks down each node in detail about how it works.
by jason
If you have made some investments in cryptocurrency, this workflow will allow you to create an Airtable base that will update the value of your portfolio every hour. You can then track how well your investments are doing. You can check out my Airtable base to see how it works or even copy my base so that you can customize this workflow for yourself. To implement this workflow, you will need to update the Airtable nodes with your own credentials and make sure that they are pointing to your Airtable