Workflow Templates

🎯 Automated TikTok Influencer Discovery & Analysis A complete n8n automation that discovers TikTok influencers using Bright Data, evaluates their fit using Claude AI, and sends personalized outreach emails. Designed for marketing teams and brands that need a scalable, intelligent way to find and connect with relevant creators. 📋 Overview This workflow provides a full-service influencer discovery pipeline: it finds TikTok profiles using search keywords, uses AI to assess alignment with your brand, and initiates contact with qualified influencers. Ideal for influencer marketing, brand partnerships, and campaign planning. ✨ Key Features 🔍 Keyword-Based Discovery** Locate TikTok influencers by specific niche-related keywords. 📊 Bright Data Integration** Access accurate TikTok profile data from Bright Data’s datasets. 🤖 AI-Powered Analysis** Claude AI evaluates each profile's fit with your brand based on bio, content, and more. 📧 Smart Email Notifications** Sends tailored outreach emails to creators deemed highly relevant. 📈 Data Storage** Google Sheets stores profile details, AI evaluation results, and outreach status. 🎯 Intelligent Filtering** Processes only influencers who meet your criteria (e.g., 5000+ followers, industry match). ⚡ Fast & Reliable** Uses professional scraping with robust error handling. 🔄 Batch Processing** Supports bulk influencer processing through a single automated flow. 🎯 What This Workflow Does Input Search Keywords** – TikTok terms for finding niche creators Business Info** – Brand description and industry Collaboration Criteria** – Follower count minimum, niche alignment Processing Steps Form Submission TikTok Discovery via Bright Data Data Extraction and Normalization Save to Google Sheets Relevance Scoring via Claude AI Filtering Based on AI Score + Follower Count Personalized Email Outreach Output Data Points | Field | Description | Example | |---------------|------------------------------------|----------------------------------| | Profile ID | TikTok profile identifier | tiktoker123456 | | Username | TikTok handle | @creativecreator | | URL | Profile link | https://tiktok.com/@creativecreator | | Description | Creator bio | "Fashion & lifestyle content..." | | Followers | Total follower count | 50,000 | | Collaboration | AI assessment of brand fit | "Highly Relevant" | | Analysis | 50-word Claude AI relevance summary| "Strong alignment with fashion..."| 🚀 Setup Instructions Prerequisites n8n (cloud or self-hosted) Bright Data account with TikTok access Google Sheets + Gmail Anthropic Claude API key 10–15 minutes setup time Step-by-Step Setup Import Workflow via JSON in n8n Configure Bright Data – Add API credentials and dataset ID Google Sheets – Setup credentials and map columns Claude AI – Insert API key and select desired model Gmail – Authenticate Gmail and update mail node settings Update Variables – Replace placeholders with business info Test & Launch – Submit a sample form and verify all outputs 📖 Usage Guide Adding Search Keywords Submit the form with search terms, business description, and industry category to trigger the workflow. Understanding AI Analysis Emails are sent only if: Collaboration status = Highly Relevant Follower count ≥ 5000 Industry alignment confirmed Claude AI returns a 50-word analysis justifying the match Customizing Filters Edit the "Find the Collaborator" prompt to adjust: Follower thresholds Industry relevance Additional metrics (e.g., engagement rate) Viewing Results Google Sheets log includes: Influencer metadata AI scores and rationale Collaboration status Email delivery timestamp 🔧 Customization Options Add More Fields:** Engagement rate, contact email, content themes Email Personalization:** Customize message templates or integrate other mail services Enhanced Filtering:** Use engagement rates, region, content frequency 🚨 Troubleshooting | Issue | Fix | |-------|-----| | Bright Data fails | Recheck API and dataset ID | | No influencer data | Adjust keywords or dataset scope | | Sheets permission error | Re-authenticate and check sharing | | Claude fails | Validate API key and prompt | | Emails not sent | Re-auth Gmail or update recipient field | | Form not triggering | Reconfirm webhook URL and permissions | Advanced Debugging Check n8n execution logs Run individual nodes for pinpointing failures Confirm all data formats Handle API rate limits Add error-catch nodes for retries 📊 Use Cases & Examples Brand Discovery:** Fashion, tech, fitness creators Competitor Insights:** Find influencers used by rival brands Campaign Planning:** Build targeted influencer lists Market Research:** Identify creator trends across regions ⚙️ Advanced Configuration Batch Execution:** Process multiple keywords with delay logic Engagement Metrics:** Scrape and calculate likes-to-follower ratios CRM Integration:** Sync qualified profiles to HubSpot, Salesforce, or Slack 📈 Performance & Limits Processing Time:** 3–5 minutes per keyword Concurrency:** 3–5 simultaneous fetches (depends on plan) Accuracy:** >95% influencer data reliability Success Rate:** 90%+ for outreach and processing

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow scrapes job listings on indeed via Apify, automatically gets that dataset, extracts information about the listing filters jobs off relevance, finds a decision maker at the company and updates a database (google sheets) with that info for outreach. All you need to do is run Apify actor then the database will update with the processed data. Benefits: Complete Job search Automation - A webhook monitors the Apify actor which sends a integration and starts the process AI-Powered Filter - Uses ChatGPT to analyze content/context, identify company goals, and filters based on job description Smart Duplicate Prevention - Automatically tracks processed job listings in a database to avoid redundancy Multi-Platform Intelligence - Combines Indeed scraping, web research via Tavily, and enriches each listing Niche Focus - Process content from multiple niches 6 currently (hardcoded) but can be changed to fit other niches (just prompt the "job filter" node) How It Works: Indeed Job Discovery: Search and apply filter for relevant job listings, copy and use URL in Apify Uses Apify's Indeed job scraper to scrape job listings from the URL of interest Automatically scrapes the information, stores it in a dataset and initiates a integration Oncoming Data Processing: Loops over 500 items (can be changed) with a batch size of 55 items (can be changed) to avoid running into API timeouts. Multiple filters to ensure all fields are scrapped with our required metrics (website must exist and number of employees < 250) Duplicate job listings are removed from oncoming batch to be processed Job Analysis & Filter: An additional filter to remove any job listing from the oncoming batch if it already exists in the google sheets database Then all new job listings gets pasted to chatGPT which uses information about the job post/description to determine if it is relevant to us All relevant jobs get a new field "verdict" which is either true or false and we keep the ones where verdict is true Enrich & Update Database: Uses Tavily to search for a decision maker (doesn't always finds one) and populate a row in google sheet with information about the job listing, the company and a decision maker at that company. Waits for 1 minute and 30 seconds to avoid google sheets and chatGPT API timeouts then loops back to the next batch to start filtering again until all job listings are processed Required Google Sheets Database Setup: Before running this workflow, create a Google Sheets database with these exact column headers: Essential Columns: jobUrl - Unique identifier for job listings title - Position Title descriptionText - Description of job listing hiringDemand/isHighVolumeHiring - Are they hiring at high volume? hiringDemand/isUrgentHire - Are they hiring at high urgency? isRemote - Is this job remote? jobType/0 - Job type: In person, Remote, Part-time, etc. companyCeo/name - CEO name collected from Tavily's search icebreaker - Column for holding custom icebreakers for each job listing (Not completed in the workflow. I will upload another that does this called "Personalized IJSFE") scrapedCeo - CEO name collected from Apify Scraper email - Email listed on for job listing companyName - Name of company that posted the job companyDescription - Description of the company that posted the job companyLinks/corporateWebsite - Website of the company that posted the job companyNumEmployees - Number of employees the company listed that they have location/country - Location of where the job is to take place salary/salaryText - Salary on job listing Setup Instructions: Create a new Google Sheet with these column headers in the first row Name the sheet whatever you please Connect your Google Sheets OAuth credentials in n8n Update the document ID in the workflow nodes The merge logic relies on the id column to prevent duplicate processing, so this structure is essential for the workflow to function correctly. Feel free to reach out for additional help or clarification at my gmail: terflix45@gmail.com and I'll get back to you as soon as I can. Set Up Steps: Configure Apify Integration: Sign up for an Apify account and obtain API key Get indeed job scraper actor and use Apify's integration to send a HTTP request to your n8n webhook (if test URL doesn't work use production URL) Use Apify node with Resource: Dataset, Operation: Get items and use your Api key as your credentials Set Up AI Services: Add OpenAI API credentials for job filtering Add Tavily API credentials for company research Set up appropriate rate limiting for cost control Database Configuration: Create Google Sheets database with provided column structure Connect Google Sheets OAuth credentials Configure the merge logic for duplicate detection Content Filtering Setup: Customize the AI prompts for your specific niche, requirements or interest Adjust the filtering criteria to fit your needs

This workflow sends a message to a Discord channel when a new row is added or a row is updated in a Google Sheet. The message will send all data rows in the Google Sheet. Prerequisites Discord account and Discord credentials. Google account and Google credentials. How it works Using a code node, we can use the obtained Google Sheet data to create a custom message that will be sent to Discord. The message will be sent to the Discord channel specified in the Discord node. Setup This workflow requires that you set up a Discord webhook and have an existing Google Sheet with data. See how to set up a Discord webhook here.

Universal Digital Device Support Assistant Transform any device manual into an intelligent AI assistant that provides 24/7 support for your users. This template works with ANY household appliance, electronic device, or technical equipment. 🎯 Use Cases Manufacturers**: Provide instant support for your products Support Teams**: Reduce ticket volume with AI-powered answers Smart Homes**: Centralized help for all devices Personal Use**: Never lose a manual again ✨ Features Universal Compatibility**: Works with any device type Multi-Language Support**: Serve global customers Intelligent Search**: Semantic understanding of user queries Context Awareness**: Remembers conversation history Easy Setup**: Just upload your manual and go 🛠️ What's Included Webhook Endpoint: Receive user queries via API AI Agent: Processes questions intelligently Vector Database: Stores and searches manuals Memory System: Maintains conversation context Upload Pipeline: Easy manual ingestion 📋 Setup Instructions Add Your Credentials: OpenAI API key (or alternative LLM) Pinecone API key (or alternative vector DB) Upload Device Manuals: Use the manual upload trigger Paste manual text or upload PDF System automatically indexes content Configure Webhook: Set your preferred endpoint path Enable CORS if needed Deploy and share URL Optional Customization: Adjust chunk size for your content Modify system prompts for your brand Add additional tools or integrations 🔧 Supported Devices (Examples) Kitchen Appliances (ovens, dishwashers, coffee machines) Home Entertainment (TVs, sound systems, gaming consoles) Smart Home Devices (thermostats, cameras, lights) Computer Equipment (printers, routers, monitors) Power Tools & Garden Equipment Medical Devices And many more! 🌐 Integration Options Embed in your website Connect to chat platforms Mobile app integration Voice assistant compatibility Email support automation 📈 Benefits Reduce support costs by 70% Available 24/7 in multiple languages Consistent, accurate responses Scales infinitely Improves with usage 🔐 Privacy & Security Your data stays in your control Can be deployed on-premise GDPR compliant architecture No data sharing between devices 💡 Pro Tips Upload manuals in sections for better accuracy Include troubleshooting guides and FAQs Add model numbers and specifications Regular updates keep content fresh Start providing world-class device support today!

Description 📄 Turn your Slack workspace into a smart AI-powered HelpDesk using this workflow. This automation listens to Slack messages and uses an AI assistant (powered by OpenAI or any other LLM) to respond to employee questions about HR, IT, or internal policies by referencing your internal documentation (such as the Policy Handbook). If the answer isn't available, it can optionally email the relevant department (HR or IT) and ask them to update the handbook. It remembers recent messages per user, cleans up intermediate responses to keep Slack threads tidy, and ensures your team gets consistent and helpful answers—without manually searching docs or escalating simple questions. Perfect for growing teams who want to streamline internal support using n8n, Slack, and AI. How it works 🛠️ This workflow turns n8n into a Slack-based HelpDesk assistant powered by AI. It listens to Slack messages using the Events API, detects whether a real user is asking a question, and responds using OpenAI (or another LLM of your choice). Here's how it works step-by-step: Webhook Trigger: The workflow starts when a message is posted in Slack via the Events API. It filters out any messages from bots to avoid loops. Identify the User: It fetches the full Slack profile of the user who posted the message and stores their name. Send Receipt Message: An initial message is sent to the user saying, “I’m on it!”, confirming their request is being processed. AI Response Handling: The message is processed using the OpenAI Chat model (GPT-4o by default). Before responding, it checks if the query matches any HR or IT policy from the Policy Handbook. If the question can’t be answered based on internal data, it can optionally alert the HR or IT department via Gmail (after user confirmation). Memory Retention: It keeps track of the last 5 interactions per user using Simple Memory, so it remembers previous context in a Slack conversation. Cleanup and Final Reply: It deletes the initial receipt message and sends a final, clean response to the user. How to use 🚀 Clone the Workflow: Download or import the JSON workflow into your n8n instance. Connect Your Credentials: Slack API (for messaging) Google Sheets API (for department contact info) Google Docs API (for the Policy Handbook) Gmail API (optional, for notifying departments) OpenAI or another AI model Slack Setup: Set up a Slack App and enable the Events API. Subscribe to message events and point them to the Webhook URL generated by the workflow. Customize Responses: Edit the initial and final Slack message nodes if you want to personalize the wording. Swap out the LLM (ChatGPT) with your preferred model in the AI Agent node. Adjust AI Behavior: Tune the prompt logic in the “AI Agent” node if you want the AI to behave differently or access different data sources. Expand Memory or Integrations: Use external databases to store longer histories. Integrate with tools like Asana, Notion, or CRM platforms for further automation. Requirements 📋 n8n (self-hosted or cloud) Slack Developer Account & App OpenAI (or any LLM provider) Google Sheets with department contact details Google Docs containing the policy Handbook Gmail account (optional, for email alerts) Knowledge of Slack Events API setup

🛒 Monitor Google Shopping Prices with Bright Data & Email Alerts This template requires a self-hosted n8n instance to run. A comprehensive n8n automation that monitors product prices daily using Bright Data's Google Shopping dataset and sends smart email alerts when price conditions are met. 📋 Overview This workflow provides an automated price monitoring solution that tracks product prices from Google Shopping daily and sends intelligent email notifications. Perfect for e-commerce monitoring, competitor analysis, deal hunting, and inventory management. ✨ Key Features 🕘 Scheduled Monitoring: Daily automated price checks at 9 AM 🛍️ Google Shopping Integration: Uses Bright Data's dataset for accurate pricing 📊 Smart Price Comparison: Compares current prices with historical data 📧 Intelligent Alerts: Sends emails only when prices meet criteria 📈 Data Storage: Updates Google Sheets with latest pricing data 🔄 Batch Processing: Handles multiple products with rate limiting ⚡ Fast & Reliable: Built-in error handling 🎯 Customizable Filters: Advanced price comparison logic 🎯 What This Workflow Does Schedule Trigger: Runs daily at 9 AM Data Retrieval: Fetches product list from Google Sheets Price Extraction: Scrapes current prices using Bright Data Data Update: Updates Google Sheets with new prices Price Comparison: Compares new vs. old prices Smart Filtering: Filters products that meet alert criteria Email Notifications: Sends alerts for qualifying changes Rate Limiting: Adds delay between emails Output Data Points | Field | Description | Example | | :------------ | :------------------------- | :------------------------------- | | Product URL | Original Google Shopping URL | https://shopping.google.com/product/... | | Product Name | Product title | iPhone 15 Pro Max 256GB | | Ratings | Product rating score | 4.5 | | Reviews | Number of reviews | 1,247 | | Old Price | Previous price | $1,199.00 | | New Price | Current scraped price | $1,199.00 | | Timestamp | When the check occurred | 2025-05-30T09:00:00Z | 🚀 Setup Instructions Prerequisites n8n instance (self-hosted or cloud) Google account with Sheets access Bright Data account with Google Shopping dataset access Gmail account for notifications Steps Import the workflow JSON into n8n Configure Bright Data credentials and dataset access Set up Google Sheets with required columns Configure Gmail OAuth2 credentials Update sheet IDs and schedule settings Test with sample products and activate 📖 Usage Guide Google Sheet Structure Your Google Sheet should have the following columns to ensure the workflow functions correctly: Product URL** (Text): The direct URL to the Google Shopping product page. This is the primary identifier for the product. Product Name** (Text): The name of the product. This will be automatically populated or updated by the workflow. Old Price** (Number/Currency): The price of the product from the previous check. This column is crucial for price comparison. New Price** (Number/Currency): The most recently scraped price of the product. Ratings** (Number): The star rating of the product. Reviews** (Number): The total number of reviews for the product. Timestamp** (Datetime): The date and time when the price check was performed. Adding Products Add Google Shopping URLs to your Google Sheet. The workflow will fetch product details and track prices. Historical price data builds over time. Understanding Price Alerts The default setting for this workflow is to send an email alert when the new price equals the old price. This might seem counterintuitive, but it's useful for specific scenarios, such as: Monitoring stable pricing:** If you are tracking a product and want to be notified when its price has remained consistent over time, indicating a potential stable buying opportunity or a benchmark. Verifying data consistency:** To confirm that the scraping process is working correctly and consistently retrieving the same price when no changes are expected. You can easily customize the alert logic to trigger on different conditions as described below. Customizing Alert Logic Price drops:** new_price < old_price Significant drops:** new_price < (old_price * 0.9) (e.g., price dropped by more than 10%) Price increases:** new_price > old_price Any change:** new_price != old_price Reading the Results Real-time pricing data Historical tracking Product metadata Timestamps for each check 🔧 Customization Options Add More Data:** Descriptions, availability, seller info, shipping, images Modify Email Templates:** Customize subject and body Multiple Recipients:** Duplicate email node and change recipients Webhook Integration:** Add real-time triggers or Slack alerts 🚨 Troubleshooting Bright Data connection failed:** Check API credentials and dataset access No price data extracted:** Verify URLs and test with different products Google Sheets permission denied:** Re-authenticate and check sharing Emails not sending:** Re-auth Gmail OAuth and verify recipients Filter not working:** Check price formats and logic Workflow failed:** Check logs, retry logic, and network status 📊 Use Cases & Examples E-commerce Monitoring:** Track competitor pricing and trends Deal Hunting:** Get alerts for price drops on wishlist items Inventory Management:** Monitor supplier pricing for procurement Market Research:** Analyze pricing trends and generate reports ⚙️ Advanced Configuration Batch Processing:** Increase batch size, add delays, use parallel processing Price History:** Store historical data, calculate averages, forecast trends Tool Integration:** CRM, Slack, databases, BI tools (Tableau, Power BI) 📈 Performance & Limits Single URL:** 2–5 seconds Concurrent Requests:** 3–5 (depends on Bright Data plan) Data Accuracy:** 95%+ Success Rate:** 90%+ Daily Capacity:** 100–500 products Memory:** ~100MB per execution API Calls:** 1 Bright Data + 2 Google Sheets per product 🤝 Support & Community n8n Forum:** <https://community.n8n.io> Documentation:** <https://docs.n8n.io> Bright Data Support:** Via your Bright Data dashboard GitHub Issues:** Report bugs and request features 🎯 Ready to Use! Your workflow provides a solid foundation for automated price monitoring. Customize it to fit your specific needs and use cases for maximum effectiveness in tracking Google Shopping prices with intelligent email notifications. Please note that this template uses Community Nodes. Ensure you understand the risks before using community nodes.

AI Automated "Viral Style" Carousels Generator for Instagram, TikTok, LinkedIn, or X 🚀 Overview Automate your social media content creation with this powerful n8n workflow! Generate engaging, viral-style carousels for Instagram, TikTok, LinkedIn, or X (Twitter) in minutes. This template leverages AI (xAI Grok) to craft compelling, high-retention text and uses n8n's Edit Image node to automatically design your slides with your custom branding. Output examples: ✨ Features AI-Powered Content:** Utilizes xAI Grok to generate witty, substantive, 7-slide carousel content based on a theme and CTA. Multi-Platform Ready:* Perfect for *Instagram carousels, **TikTok carousels, LinkedIn carousels, and X (Twitter) threads. Automated Design:** Overlays AI-generated text onto your chosen background image, creating visually consistent slides. Easy Customization:** Adapt the AI persona, font styles, colors, and background images to match your brand. Google Drive Integration:** Seamlessly downloads your background template and uploads finished carousel slides. No Code Automation:** Set up once and generate endless content with minimal effort. 💡 How it Works Input Trigger: Provide a theme and call to action (CTA) via a webhook or manual trigger. Content Generation: The AI (acting as "The Carousel Cynic") writes 7 distinct slides, each with a provocative title and a detailed description, formatted for maximum engagement. Image Assembly: Downloads a base background image from Google Drive. Loops through each of the 7 AI-generated slides. Uses the Edit Image node to dynamically add the slide's title and description to the background. Outputs sequentially numbered .png files (e.g., 1.png, 2.png). Output & Storage: Uploads all final carousel images to a specified folder in your Google Drive, ready for publishing. 🛠️ Setup Steps xAI Credentials: Add your xAI API Key to the xAI Grok Chat Model node. Google Drive Integration: Connect your Google Drive OAuth2 credentials. In the Download file node, update the File ID to point to your desired blank background image. In the Upload file node, select the Google Drive folder where you want to save the generated carousels. Customization (Optional): Adjust AI persona in the AI Agent node's "System Prompt." Modify fontSize, fontColor, positionX, and positionY in the Params Style Config node to perfectly align text on your background images. 🎁Bonus Added in workflow a Canva link to editable background style I use in my carousels. 🔑 Keywords AI, Automation, Social Media, Carousel, Instagram, TikTok, LinkedIn, X, Twitter, Content Creation, Viral Content, Marketing, Grok, xAI, Image Generation, No-code, Workflow, Productivity, Creator Economy, Digital Marketing, Engagement, Visual Content, Dynamic Image, Automated Marketing.

Complete MCP server exposing 2 Analytics API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Analytics API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Analytics API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath} • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Rate_Limit (1 endpoints) • GET /rate_limit/: Retrieve Application Rate Limits 🔧 User_Rate_Limit (1 endpoints) • GET /user_rate_limit/: Retrieve User Rate Limits 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Analytics API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

📧 Email Validation Workflow Using APILayer API This n8n workflow enables users to validate email addresses in real time using the APILayer Email Verification API. It's particularly useful for preventing invalid email submissions during lead generation, user registration, or newsletter sign-ups, ultimately improving data quality and reducing bounce rates. ⚙️ Step-by-Step Setup Instructions Trigger the Workflow Manually: The workflow starts with the Manual Trigger node, allowing you to test it on demand from the n8n editor. Set Required Fields: The Set Email & Access Key node allows you to enter: email: The target email address to validate. access_key: Your personal API key from apilayer.net. Make the API Call: The HTTP Request node dynamically constructs the URL: https://apilayer.net/api/check?access_key={{ $json.access_key }}&email={{ $json.email }} It sends a GET request to the APILayer endpoint and returns a detailed response about the email's validity. (Optional): You can add additional nodes to filter, store, or react to the results depending on your needs. 🔧 How to Customize Replace the manual trigger with a webhook or schedule trigger to automate validations. Dynamically map the email and access_key values from previous nodes or external data sources. Add conditional logic to filter out invalid emails, log them into a database, or send alerts via Slack or Email. 💡 Use Case & Benefits Email validation is crucial in maintaining a clean and functional mailing list. This workflow is especially valuable in: Sign-up forms where real-time email checks prevent fake or disposable emails. CRM systems to ensure user-entered emails are valid before saving them. Marketing pipelines to minimize email bounce rates and increase campaign deliverability. Using APILayer’s trusted validation service, you can verify whether an email exists, check if it’s a role-based address (like info@ or support@), and identify disposable email services—all with a simple workflow. Keywords: email validation, n8n workflow, APILayer API, verify email, real-time email check, clean email list, reduce bounce rate, data accuracy, API integration, no-code automation

This guide walks you through setting up an automated workflow that compares live flight fares across multiple booking platforms (e.g., Skyscanner, Akasa Air, Air India, IndiGo) using API calls, sorts the results by price, and sends the best deals via email. Ready to automate your flight fare comparison process? Let’s get started! What’s the Goal? Automatically fetch and compare live flight fares from multiple platforms using scheduled triggers. Aggregate and sort fare data to identify the best deals. Send the comparison results via email for review or action. Enable 24/7 fare monitoring with seamless integration. By the end, you’ll have a self-running system that delivers the cheapest flight options effortlessly. Why Does It Matter? Manual flight fare comparison is time-consuming and often misses the best deals. Here’s why this workflow is a game-changer: Zero Human Error**: Automated data fetching and sorting ensure accuracy. Time-Saving Automation**: Instantly compare fares across platforms, boosting efficiency. 24/7 Availability**: Monitor fares anytime without manual effort. Cost Optimization**: Focus on securing the best deals rather than searching manually. Think of it as your tireless flight fare assistant that always finds the best prices. How It Works Here’s the step-by-step magic behind the automation: Step 1: Trigger the Workflow Set Schedule Node**: Triggers the workflow at a predefined schedule to check flight fares automatically. Captures the timing for regular fare updates. Step 2: Process Input Data Set Input Data Node**: Sets the input parameters (e.g., origin, destination, departure date, return date) for flight searches. Prepares the data to be sent to various APIs. Step 3: Fetch Flight Data Skyscanner API Node**: Retrieves live flight fare data from Skyscanner using its API endpoint. Akasa Air API Node**: Fetches live flight fare data from Akasa Air using its API endpoint. Air India API Node**: Collects flight fare data directly from Air India’s API. IndiGo API Node**: Gathers flight fare data from IndiGo’s API. Step 4: Merge API Results Merge API Data Node**: Combines the flight data from Skyscanner and Akasa Air into a single dataset. Merge Both API Data Node**: Merges the data from Air India and IndiGo with the previous dataset. Merge All API Results Node**: Consolidates all API data into one unified result for further processing. Step 5: Analyze and Sort Compare Data and Sorting Price Node**: Compares all flight fares and sorts them by price to highlight the best deals. Step 6: Send Results Send Response via Email Node**: Sends the sorted flight fare comparison results to the user via email for review or action. How to Use the Workflow? Importing this workflow in n8n is a straightforward process that allows you to use this pre-built solution to save time. Below is a step-by-step guide to importing the Flight Fare Comparison Workflow in n8n. Steps to Import a Workflow in n8n Obtain the Workflow JSON Source the Workflow: The workflow is shared as a JSON file or code snippet (provided earlier or exported from another n8n instance). Format: Ensure you have the workflow in JSON format, either as a file (e.g., workflow.json) or copied text. Access the n8n Workflow Editor Log in to n8n: Open your n8n instance (via n8n Cloud or self-hosted). Navigate to Workflows: Go to the Workflows tab in the n8n dashboard. Open a New Workflow: Click Add Workflow to create a blank workflow. Import the Workflow Option 1: Import via JSON Code (Clipboard): In the n8n editor, click the three dots (⋯) in the top-right corner to open the menu. Select Import from Clipboard. Paste the JSON code (provided earlier) into the text box. Click Import to load the workflow. Option 2: Import via JSON File: In the n8n editor, click the three dots (⋯) in the top-right corner. Select Import from File. Choose the .json file from your computer. Click Open to import the workflow. Setup Notes API Credentials**: Configure each API node (Skyscanner, Akasa Air, Air India, IndiGo) with the respective API keys and endpoints. Check the API provider’s documentation for details. Email Integration**: Authorize the Send Response via Email node with your email service (e.g., Gmail SMTP settings or an email API like SendGrid). Input Customization**: Adjust the Set Input Data node to include specific origin/destination pairs and date ranges as needed. Schedule Configuration**: Set the desired frequency in the Set Schedule node (e.g., daily at 9 AM IST). Example Input Send a POST request to the workflow (if integrated with a webhook) with: { "origin": "DEL", "destination": "BOM", "departureDate": "2025-08-01", "returnDate": "2025-08-07" } Optimization Tips Error Handling**: Add IF nodes to manage API failures or rate limits. Rate Limits**: Include a Wait node if APIs have strict limits. Data Logging**: Add a node (e.g., Google Sheets) to log all comparisons for future analysis. This workflow transforms flight fare comparison into an automated, efficient process, delivering the best deals directly to your inbox!

Build a Redis-Powered CRUD App with HTML Frontend This workflow demonstrates how to use n8n to build a complete, self-contained CRUD (Create, Read, Update, Delete) application without relying on any external server or hosting. It not only acts as the backend, handling all CRUD operations through Webhook endpoints, but also serves a fully functional HTML Single Page Application (SPA) directly via a webhook response. Redis is used as a lightweight data store, providing fast and simple key-value storage with auto-incremented IDs. Because both the frontend (HTML app) and backend (API endpoints) are managed entirely within a single n8n workflow, you can quickly prototype or deploy small tools without additional infrastructure. This approach is ideal for: Rapidly creating no-code or low-code applications Running fully browser-based tools served directly from n8n Teaching or demonstrating n8n + Redis integration in a single workflow Features Add new item with auto-incremented ID Edit existing item Delete specific item Reset all data (clear storage and reset autoincrement id) Single HTML frontend for demonstration (no framework required) Setup Instructions 1. Prerequisites Before importing and running the workflow, make sure you have: A running n8n instance (self-hosted or cloud) A running Redis server (local or remote) 2. API Path Setup For the REST API, use a consistent path. For example, if you choose items as the path: 2a. Get All Items** Method: GET Endpoint: items 2b. Add Item** Method: POST Endpoint: items 2c. Edit Item** Method: PUT Endpoint: items 2d. Delete Item** Method: DELETE Endpoint: items 2e. Reset Items** Method: POST Endpoint: items-reset 3. Configure the API URL Set the API URL in the SET API URL node. Use your n8n webhook URL, for example: https://yourn8n.com/webhook/items 4. Run the HTML App Once everything is set: Open the webhook URL for the HTML app in a browser. The CRUD interface will load and connect to the API endpoints automatically. You can now add, edit, delete, or reset items directly from the web interface. Workflows 1. Render the HTML CRUD App This webhook serves a self-contained HTML Single Page Application (SPA) for basic CRUD operations. The HTML content is returned directly in the webhook response. This setup is ideal for lightweight, browser-based tools without external hosting. How to Use Open the webhook URL in a browser The CRUD interface will load and connect to the data source via API calls Before using, make sure to edit the api_url in the SET API URL node to match your webhook endpoint 2a. REST API: Get All Items This webhook handles retrieving all saved items from Redis. Each item is returned with its corresponding ID and associated data (e.g., name). This endpoint is used by the HTML CRUD App to display the full list of items. Method**: GET Function**: Fetches all items stored in Redis and returns them as a JSON array 2b. REST API: Add Item This webhook handles the Add Item functionality. This endpoint is typically called by the HTML CRUD App when adding a new item. Method**: POST Request Body**: { "name": "item name" } Function**: Generates an auto-incremented ID using Redis and saves the data under that ID 2c. REST API: Edit Item This webhook handles updating an existing item in Redis. Method**: PUT Request Body**: { "id": 1, "name": "Updated Item Name" } Function**: Finds the item by the given id and updates its data in Redis 2d. REST API: Delete Item This webhook handles deleting a specific item from Redis. Method**: DELETE Request Body**: { "id": 1 } Function**: Removes the item with the given id from Redis 2e. REST API: Reset Items This webhook handles resetting all data in the application. Method**: POST Function**: Deletes all stored items from Redis Resets the auto-increment ID by deleting the data in Redis

SEO Blog Generator with GPT-4o, Perplexity, and Telegram Integration This workflow helps you automatically generate SEO-optimized blog posts using Perplexity.ai, OpenAI GPT-4o, and optionally Telegram for interaction. 🚀 Features 🧠 Topic research via Perplexity sub-workflow ✍️ AI-written blog post generated with GPT-4o 📊 Structured output with metadata: title, slug, meta description 📩 Integration with Telegram to trigger workflows or receive outputs (optional) ⚙️ Requirements ✅ OpenAI API Key (GPT-4o or GPT-3.5) ✅ Perplexity API Key (with access to /chat/completions) ✅ (Optional) Telegram Bot Token and webhook setup 🛠 Setup Instructions Credentials: Add your OpenAI credentials (openAiApi) Add your Perplexity credentials under httpHeaderAuth Optional: Setup Telegram credentials under telegramApi Inputs: Use the Form Trigger or Telegram input node to send a Research Query Subworkflow: Make sure to import and activate the subworkflow Perplexity_Searcher to fetch recent search results Customization: Edit prompt texts inside the Blog Content Generator and Metadata Generator to change writing style or target industry Add or remove output nodes like Google Sheets, Notion, etc. 📦 Output Format The final blog post includes: ✅ Blog content (1500-2000 words) ✅ Metadata: title, slug, and meta description ✅ Extracted summary in JSON ✅ Delivered to Telegram (if connected) Need help? Reach out on the n8n community forum