Workflow Templates

📄 What this workflow does This workflow automatically turns any uploaded video into structured blog research using AI tools. It transcribes the video, extracts keywords, runs research based on those keywords, and saves the final result to a Google Sheet. It uses Dumpling AI for transcription and research, OpenAI for keyword extraction, and Google Sheets for organizing the output. 👤 Who is this for This workflow is perfect for: Content creators who repurpose video content into blog posts SEO and marketing teams looking to extract topics and keyword insights from video materials Anyone who wants to automate video-to-text and research workflows without doing it manually ✅ Requirements Google Drive** account with a folder to watch for video uploads Dumpling AI** API access for transcription and agent research OpenAI (GPT-4o)** credentials for keyword extraction Google Sheets** document with the following column headers: Keywords topicsFromPerplexity blogPostsFromGoogle ⚙️ How to set up Connect your Google Drive and choose the folder where videos will be uploaded. Set up your Dumpling AI and OpenAI GPT-4o API credentials. Create a Google Sheet with the required columns. Replace the default folder ID and spreadsheet ID in the workflow with your own. Activate the workflow to start watching for new videos. 🔁 How it works (Workflow Steps) Watch Uploaded Videos: Triggers when a new video is added to your selected Google Drive folder. Download Video: Downloads the uploaded video file. Convert Video to Base64: Prepares the video for API submission by converting it to base64. Transcribe with Dumpling AI: Sends the video to Dumpling AI to get a full transcript. Extract Keywords with OpenAI: Analyzes the transcript and extracts five key SEO keywords. Run Competitor Research via Dumpling AI: Uses those keywords to fetch related topics and blog examples from Perplexity and Google. Format Results for Google Sheets: Formats the research results into clean text blocks. Append to Google Sheets: Saves the data into your specified Google Sheet. 🛠️ Customization Ideas Add a translation step after transcription to support multilingual content research. Modify the GPT prompt to extract summaries or titles instead of keywords. Change the Google Sheet structure to log video filenames and timestamps. Add email or Slack notifications to alert you when research is complete.

Verified Beta Tester Access Kit - Automated Onboarding System Transform Your Beta Testing Program Automate your entire beta tester onboarding process from signup to tracking with this comprehensive, production-ready n8n workflow. 📚 CATEGORY TAGS Primary Category: ✅ Marketing & Sales Additional Tags: Automation Email Marketing User Management Onboarding SaaS Product Launch Beta Testing Access Control What This Workflow Does When a beta tester signs up through your form or API, this workflow automatically: ✅ Verifies Email Authenticity - Uses VerifiEmail API to validate addresses and block disposable emails ✅ Generates Unique Access Codes - Creates secure BETA-XXXXXX codes with timestamps ✅ Creates QR Codes - Generates scannable codes for quick mobile activation ✅ Builds Branded Access Cards - Produces professional HTML/CSS cards with tester details ✅ Converts to Images - Transforms cards into shareable PNGs ✅ Sends Welcome Emails - Delivers beautifully formatted emails via Gmail ✅ Logs in Trello - Creates organized tracking cards automatically ✅ Returns API Responses - Sends success/error responses with complete data Complete execution time: 5-10 seconds per signup Perfect For 🚀 SaaS startups launching beta programs 📱 Mobile app developers managing beta testers 🎮 Game studios running closed beta tests 🏢 Enterprise teams controlling early access 💼 Product managers organizing user testing 🔬 Research projects managing participants Key Features Security First Real-time email validation Blocks disposable email addresses Unique, non-guessable access codes Webhook authentication ready Professional Branding Customizable HTML/CSS templates Embedded QR codes Responsive email design High-quality PNG generation Team Collaboration Automatic Trello card creation Organized tracking boards Checklist items for follow-ups Easy team assignments Production Ready Comprehensive error handling Detailed logging Scalable architecture Easy integration What You'll Need Required API Keys (All Have Free Tiers): VerifiEmail - Email verification at https://verifi.email HTMLCSSToImage - Image generation at https://htmlcsstoimg.com Gmail Account - Email delivery Trello Account - Project tracking at https://trello.com/app-key Workflow Steps Webhook receives POST request with tester data VerifiEmail validates email authenticity Conditional logic routes valid/invalid emails Function generates unique BETA-XXXXXX access codes HTTP Request creates QR code image Set node stores QR code URL HTMLCSSToImage converts access card to PNG Gmail sends branded welcome email with kit Trello creates tracking card in board Webhook responds with success/error status Sample Request POST to webhook: { "tester_name": "Aarav Mehta", "tester_email": "aarav@example.com", "product_name": "YourApp v1.0", "signup_date": "2025-11-05" } Success Response (200): { "status": "success", "message": "Beta tester verified and access kit delivered", "data": { "tester_name": "Aarav Mehta", "access_code": "BETA-A7K9M2", "trello_card_created": true, "email_sent": true, "qr_code_generated": true } } Error Response (400): { "status": "error", "message": "Invalid or disposable email address detected", "reason": "Disposable email" } Customization Options Email Template Modify HTML in Gmail node Add company logo Change colors and fonts Access Card Design Edit CSS in HTMLCSSToImage node Adjust QR code size Match your brand Access Code Format Change prefix from "BETA-" to your choice Modify length and characters Trello Integration Add custom fields Include labels Set due dates Assign team members Use Cases Mobile App Beta Launch User fills form → Email verified → Code sent → App activated → Team tracks in Trello SaaS Early Access User signs up → Email validated → Access kit received → Product team manages Game Testing Campaign Player requests access → Email verified → Unique key generated → Community team tracks What Makes This Special Unlike simple email workflows, this is a complete system that handles: Security (email verification) Branding (custom access cards) Communication (professional emails) Tracking (team collaboration) Integration (webhook API) All in one cohesive, production-ready workflow! Troubleshooting Common Issues & Solutions: Webhook not receiving data → Check URL and POST method Email verification fails → Verify API key and rate limits Gmail not sending → Reconnect OAuth2 Trello card fails → Confirm List ID is correct Image not generating → Check HTMLCSSToImage credentials 🏷️ ADDITIONAL METADATA Difficulty Level: ⭐⭐⭐ Intermediate (requires API key setup) Time to Setup: 🕐 10-15 minutes

This n8n template demonstrates how to audit your brand’s visibility across multiple AI systems and automatically log the results to Google Sheets. It sends the same prompt to OpenAI, Perplexity, and (optionally) a ChatGPT web actor, then runs sentiment and brand-hierarchy analysis on the responses. Use cases are many: benchmark how often (and how positively) your brand appears in AI answers, compare responses across models, and build a repeatable “AI visibility” report for marketing and comms teams. 💡 Good to know You’ll bring your own API keys for OpenAI and Perplexity. Usage costs depend on your providers’ pricing. The optional APIfy actor automates the ChatGPT web UI and may violate terms of service. Use strictly at your own risk. ⁉ How it works A Manual Trigger starts the workflow (you can replace it with any trigger). Input prompts are read from a Google Sheet (or you can use the included “manual input” node). The prompt is sent to three tools: -- OpenAI (via API) to check baseline LLM knowledge. -- Perplexity (API) to retrieve an answer with citations. -- Optionally, an APIfy actor that scrapes a ChatGPT response (web interface). Responses are normalized and mapped (including citations where available). An LLM-powered sentiment pass classifies each response into: -- Basic Polarity: Positive, Neutral, or Negative -- Emotion Category: Joy, Sadness, Anger, Fear, Disgust, or Surprise -- Brand Hierarchy: ordered list such as Nike>Adidas>Puma The consolidated record (Prompt, LLM, Response, Brand mentioned flag, Brand Hierarchy, Basic Polarity, Emotion Category, Source 1–3/4) is appended to your “Output many models” Google Sheet. A simplified branch shows how to take a single response and push it to a separate sheet. 🗺️ How to use Connect your Google Sheets OAuth and create two tabs: -- Input: a single “Prompt” column -- Output: columns for Prompt, LLM, Response, Brand mentioned, Brand Hierarchy, Basic Polarity, Emotion Category, Source 1, Source 2, Source 3, Source 4 Add your OpenAI and Perplexity credentials. (Optional) Add an APIfy credential (Query Auth with token) if you want the ChatGPT web actor path. Run the Manual Trigger to process prompts in batches and write results to Sheets. Adjust the included “Limit for testing” node or remove it to process more rows. ⚒️ Requirements OpenAI API access (e.g., GPT-4.1-mini / GPT-5 as configured in the template) Perplexity API access (model: sonar) Google Sheets account with OAuth connected in n8n (Optional) APIfy account/token for the ChatGPT web actor 🎨 Customising this workflow Swap the Manual Trigger for a webhook or schedule to run audits automatically. Extend the sentiment analyzer instructions to include brand-specific rules or compliance checks. Track more sources (e.g., additional models or vertical search tools) by duplicating the request→map→append pattern. Add scoring (e.g., “visibility score” per prompt) and charts by pointing the output sheet into Looker Studio or a BI tool.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This n8n template automatically parses bank transaction emails (HDFC, Indian Bank, Indian Overseas Bank, UPI apps like Google pay, Paytm, etc.) - The from email(bank name/UPI apps) is changable, classifies them using Gemini AI, and logs them into a structured Google Sheets budget tracker. It helps you consolidate expenses, compare against monthly budgets, and get real-time alerts when limits are exceeded. 📝 Problem Statement Tracking expenses manually from different bank emails and UPI apps is frustrating, time-consuming, and error-prone. Small transactions often slip through, making budget control difficult. This workflow solves that by: Automatically extracting financial data from Gmail. Categorizing expenses using AI parsing. Saving all data into Google Sheets in a structured way. Comparing with monthly budgets and raising alerts. Target Audience: Individuals who want personal budget automation. Families managing shared household spending. Small teams looking for a lightweight financial log. ⚙️ Setup Prerequisites An n8n instance (self-hosted or cloud). A Google account with Gmail + Google Sheets enabled. Pre-created Google Sheets file with 2 tabs: Expenses Budgets A configured Gemini API connection in n8n. 📊 Google Sheets Template Expenses Tab (columns in order): Timestamp | Date | Account | From | To | Type | Category | Description | Amount | Currency | Source | MessageId | Status Budget Tab (columns in order): Month | Category | Budget Amount | Notes | UpdatedAt Yearly Summary Tab (auto-calculated): Year | Month | Category | Total Expense | Budget | Variance | Alert Variance = Budget - Total Expense Alert = ⚠️ Over Budget when spending > budget 🚀 How It Works Gmail: Gmail Trigger captures new bank/UPI emails. Gemini AI Parser extracts structured details (date, amount, category, etc.). Filter Node ensures only valid financial transactions are logged. Information extractor will extract the information like Date, account, transaction type(Credit/Debit), description, currency, status, messageId, from email, to email, category -> checks if the transaction is 'Credit' or 'Debit' then appends the details to the respective google sheet Budget Validator checks against monthly allocations. If the expense is above the budget is raises an alert and will send a email to the connected account. For sending email I wrote a Google Sheet App script: var ss = SpreadsheetApp.getActiveSpreadsheet(); var monthly = ss.getSheetByName("MonthlySummary"); var yearly = ss.getSheetByName("YearlySummary"); // Get values from Monthly Summary var totalExpense = monthly.getRange("D2").getValue(); var budget = monthly.getRange("E2").getValue(); // Get current date info var now = new Date(); var month = Utilities.formatDate(now, "GMT+5:30", "MM"); var year = Utilities.formatDate(now, "GMT+5:30", "yyyy"); var status = (totalExpense > budget) ? "Alert" : ""; // Append to Yearly Summary yearly.appendRow([year, month, totalExpense, status]); // If budget exceeded, send alert email if (status === "Alert") { var emailAddress = "YOUR EMAIL"; var subject = "⚠️ Budget Exceeded - " + month + "/" + year; var body = "Your total expenses this month (" + totalExpense + ") have exceeded your budget of " + budget + ".\n\n" + "Please review your spending."; MailApp.sendEmail(emailAddress, subject, body); } // 🔄 Reset Monthly Summary var lastRow = monthly.getLastRow(); if (lastRow > 3) { // assuming headers in first 2-3 rows monthly.getRange("A4:C" + lastRow).clearContent(); } // Reset total in D2 monthly.getRange("D2").setValue(0); } Monthly summary auto-calculates the expense and updates the expense for every month and budgets(sum all budgets if there are more than 1 budgets). Yearly Summary auto-updates and raises over-budget alerts. Telegram: Takes input from a telegram bot which is connected to the n8n workflow telegram trigger. Gemini AI Parser extracts structured details (date, amount, category, etc.). Then it checks, whether the manually specified details is 'budget' or 'expense', then splits the data -> parse the data -> then again check whether it is 'Budget' or 'Expense' then appends the structured data to the respective google sheet. Monthly summary auto-calculates the expense and updates the expense for every month and budgets(sum all budgets if there are more than 1 budgets). Yearly Summary auto-updates and raises over-budget alerts. 🔧 Customization Add support for more banks/UPI apps by extending the parser schema. const senderEmail = $input.first().json.From || ""; // Account detection let account = ""; // you can modify the bank names and UPI names here if (/alerts@hdfcbank\.net/i.test(senderEmail)) account = "HDFC Bank"; // you can modify the bank names and UPI names here else if (/ealerts@iobnet\.co\.in/i.test(senderEmail)) account = "Indian Overseas Bank"; else if (/alerts@indianbank\.in/i.test(senderEmail)) account = "Indian Bank"; else if (/@upi|@okhdfcbank|@okaxis|@okicici/i.test(emailBody)) { if (/gpay|google pay/i.test(emailBody)) account = "Google Pay"; else if (/phonepe/i.test(emailBody)) account = "PhonePe"; else if (/paytm/i.test(emailBody)) account = "Paytm"; else account = "UPI"; } else { account = "Other"; } // If account is "Other", skip output if (account === "Other") { return []; } // Output return [{ account, from: senderEmail, // exact Gmail "From" metadata snippet: emailBody, messageId: $input.first().json.id || "" }]; Create custom categories (e.g., Travel, Groceries, Subscriptions). Send real-time alerts via Telegram/Slack/Email using n8n nodes. Share the Google Sheet with family or team for collaborative use. 📌 Usage The workflow runs automatically on every new Gmail transaction email and financial input on the telegram bot. At the end of each month, totals are calculated in the Yearly Summary tab. Users only need to maintain the Budget tab with updated monthly allocations.

Description Automatically generate polished, n8n-ready template descriptions from your saved JSON workflows in Google Drive. This AI-powered automation processes workflow files, drafts compliant descriptions, and delivers Markdown and HTML outputs directly to your inbox. 🚀💌📊💬 What This Template Does Manually triggers the workflow to start processing. Searches a specified Google Drive folder for JSON workflow files. Iterates through each JSON file found in that folder. Downloads each file and prepares it for data extraction. Parses workflow data from the downloaded JSON content. Uses Azure OpenAI GPT-4 to generate concise titles and detailed descriptions. Converts the AI output into structured Markdown for n8n template publishing. Creates an HTML version of the description for email delivery. Logs generated details into a Google Sheet for record-keeping. Sends an email containing the Markdown and HTML descriptions to the target recipient. Key Benefits ✅ Fully automates n8n template description creation. ✅ Ensures consistency with official n8n publishing guidelines. ✅ Saves time while eliminating human writing errors. ✅ Provides dual Markdown + HTML outputs for flexibility. ✅ Centralizes workflow metadata in Google Sheets. ✅ Simplifies collaboration and version tracking via email delivery. Features Manual workflow trigger for controlled execution. Integration with Google Drive for locating and downloading JSON files. Intelligent parsing of workflow data from JSON structure. GPT-4-powered AI for title and description generation. Automatic Markdown + HTML formatting for n8n publishing. Google Sheets integration for persistent record-keeping. Automated Gmail delivery of generated documentation. Requirements n8n instance (cloud or self-hosted). Google Drive OAuth2 credentials with file read permissions. Google Sheets OAuth2 credentials with edit permissions. Azure OpenAI GPT-4 API key for AI text generation. Gmail OAuth2 credentials for email sending. Target Audience n8n content creators documenting workflows. 👩‍💼 Automation teams handling multiple template deployments. 🔄 Agencies and freelancers managing workflow documentation. 🏢 Developers leveraging AI for faster template creation. 🌐 Technical writers ensuring polished, standardized outputs. 📊 Step-by-Step Setup Instructions Connect your Google Drive account and specify the folder containing JSON workflows. 🔑 Authorize Google Sheets and confirm access to the tracking spreadsheet. ⚙️ Add Azure OpenAI GPT-4 API credentials for AI-powered text generation. 🧠 Connect Gmail credentials for automated email delivery. 📧 Run the workflow manually using a test JSON file to validate all nodes. ✅ Enable the workflow to automatically generate and send descriptions as needed. 🚀

Automated SSL/TLS Certificate Expiry Report for AWS > Automatically generates a weekly report of all AWS ACM certificates, including status, expiry dates, and renewal eligibility. The workflow formats the data into both Markdown (for PDF export to Slack) and HTML (for email summary), helping teams stay on top of certificate compliance and expiration risks. Who’s it for This workflow is designed for DevOps engineers, cloud administrators, and compliance teams who manage AWS infrastructure and need automated weekly visibility into the status of their SSL/TLS certificates in AWS Certificate Manager (ACM). It's ideal for teams that want to reduce the risk of expired certs, track renewal eligibility, and maintain reporting for audit or operational purposes. How it works / What it does This n8n workflow performs the following actions on a weekly schedule: Trigger: Automatically runs once a week using the Weekly schedule trigger. Fetch Certificates: Uses Get many certificates action from AWS Certificate Manager to retrieve all certificate records. Parse Data: Processes and reformats certificate data (dates, booleans, SANs, etc.) into a clean JSON object. Generate Reports: 📄 Markdown Report: Uses the Certificate Summary Markdown Agent (OpenAI) to generate a Markdown report for PDF export. 🌐 HTML Report: Uses the Certificate Summary HTML Agent to generate a styled HTML report for email. Deliver Reports: Converts Markdown to PDF and sends it to Slack as a file. Sends HTML content as a formatted email. How to set up Configure AWS Credentials in n8n to allow access to AWS ACM. Create a new workflow and use the following nodes in sequence: Schedule Trigger: Weekly (e.g., every Monday at 08:00 UTC) AWS ACM → Get many certificates Function Node → Parse ACM Data: Converts and summarizes certificate metadata OpenAI Chat Node (Markdown Agent) with a system/user prompt to generate Markdown Configure Metadata → Define file name and MIME type (.md) Create document file → Converts Markdown to document stream Convert to PDF Slack Node → Upload the PDF to a channel (Optional) Add a second OpenAI Chat Node for generating HTML and sending it via email Connect Output: Markdown report → Slack file upload HTML report → Email node with embedded HTML Requirements 🟩 n8n instance (self-hosted or cloud) 🟦 AWS account with access to ACM 🟨 OpenAI API key (for ChatGPT Agent) 🟥 Slack webhook or OAuth credentials (for file upload) 📧 Email integration (e.g., SMTP or SendGrid) 📝 Permissions to write documents (Google Drive / file node) How to customize the workflow Change report frequency**: Adjust the Weekly schedule trigger to daily or monthly as needed. Filter certificates**: Modify the function node to only include EXPIRED, IN_USE, or INELIGIBLE certs. Add tags or domains to include/exclude. Add visuals**: Enhance the HTML version with colored rows, icons, or company branding. Change delivery channels**: Replace Slack with Microsoft Teams, Discord, or Telegram. Send Markdown as email attachment instead of PDF. Integrate ticketing**: Create a JIRA/GitHub issue for each certificate that is EXPIRED or INELIGIBLE.

Introduction Automates stock market analysis using multiple AI models to predict trends, analyze sentiment, and generate consensus-based investment insights. For traders and analysts seeking data-driven forecasts by eliminating manual research and combining AI perspectives for accurate predictions. How It Works Daily trigger fetches stock data, news, ratings, and sentiment → AI models analyze each source → OpenAI generates report → Three AI validators (OpenAI, Anthropic, Gemini) cross-verify → Consensus evaluation → Telegram alert with insights. Workflow Template Schedule → Fetch Stock Data → Fetch News → Fetch Ratings → Fetch Sentiment → AI Analysis → Combine → Generate Report (GPT) → Validate (3 AIs) → Evaluate Consensus → Send Telegram Workflow Steps Data Collection: Scheduled trigger fetches prices, news, analyst ratings, and social trends AI Analysis: Separate models analyze stocks, news sentiment, ratings, and social discussions Report Generation: OpenAI GPT combines analyses into comprehensive market report Multi-AI Validation: Three AI models independently validate predictions for accuracy Consensus Building: Evaluates AI agreement to determine confidence levels Alert Delivery: Sends Telegram alerts with buy/sell/hold recommendations Setup Instructions Schedule: Configure daily trigger time Data Sources: Add API keys for stock data, news APIs, and social platforms AI Models: Configure OpenAI, Anthropic, and Google Gemini credentials Telegram: Create bot and add token Thresholds: Define consensus requirements for recommendations Prerequisites Stock data API (Alpha Vantage, Yahoo Finance) News API key Social media API OpenAI API key Anthropic API key Google Gemini API key Telegram bot token Use Cases Day Trading: Real-time volatile stock analysis with multiple AI perspectives. Portfolio Management: Daily consensus reports for rebalancing. Customization Add technical indicators (RSI, MACD). Include crypto analysis. Integrate portfolio tracking. Add email/Slack notifications. Configure sector-specific analysis. Benefits Eliminates hours of daily research. Reduces AI hallucination through multi-model validation. Provides 24/7 monitoring. Combines multiple data sources.

About This Template This workflow automatically generates and sends AI-powered responses to user inquiries from a LINE Official Account. It uses RAG (Retrieval-Augmented Generation) technology to produce natural, context-aware answers based on your FAQ database (Supabase/PostgreSQL). How It Works Receive Questions: An n8n webhook receives messages from your LINE Official Account. FAQ Search: The n8n LangChain Agent analyzes the user’s question and performs a vector search on your Supabase FAQ database. It can also fetch user-specific data (e.g., reservation info) from PostgreSQL. AI Generation: The OpenAI GPT model generates a context-aware answer based on the retrieved information and conversation history. Reply: The response is sent back to the user via the LINE Messaging API. Admin Notifications: (Optional) If the AI cannot answer, the workflow can notify admins (e.g., via LINE WORKS or Slack). Who It’s For Businesses wanting to automate customer support on LINE. Developers building intelligent chatbots with existing FAQ data. Organizations aiming for 24/7 customer service. Requirements An n8n account (cloud or self-hosted) An OpenAI API key A Supabase account (for FAQ data) A PostgreSQL database (for conversation history) A LINE Official Account & Messaging API access token Setup Steps Configure Credentials: Register credentials for OpenAI, Supabase, PostgreSQL, and LINE Messaging API in n8n. Prepare Databases: Create your tables in Supabase (for FAQs) and PostgreSQL (for conversation history). Customize the Prompt: In the "RAG AI Agent" node, edit the system prompt to fit your business and tone. Set Environment Variables: Update URLs, Channel IDs, and API endpoints in the nodes to match your environment. Customization Options Change AI Model:** Select a different model (e.g., gpt-4o) in the "OpenAI Chat Model" node. Add Data Sources:** Add new "Tool" nodes (like an HTTP Request) to the "RAG AI Agent" to access other APIs (e.g., booking systems). Change Notifications:** Replace the "LINE Works" nodes with a Slack or Email node to change the admin notification channel.

Verified Gym Trial Pass with Photo ID Overview Automate gym trial pass generation with email verification, photo ID integration, QR codes, and professional PDF passes. This workflow handles the complete member onboarding process - from signup to verified pass delivery - in under 10 seconds. What This Workflow Does Receives signup data via webhook (name, email, photo URL, validity dates) Verifies email authenticity using VerifiEmail API (blocks disposable emails) Generates unique Pass ID in format GYM-{timestamp} Creates QR code for quick check-in at gym entrance Builds branded pass design with gradient styling, member photo, and validity dates Exports to PDF format for mobile-friendly viewing Sends email with PDF attachment and welcome message Logs all registrations in Google Sheets for record-keeping Returns API response with complete pass details Key Features ✅ Email Verification - Blocks fake and disposable email addresses ✅ Photo ID Integration - Displays member photo on digital pass ✅ QR Code Generation - Instant check-in scanning capability ✅ Professional Design - Gradient purple design with modern styling ✅ PDF Export - Mobile-friendly format that members can save ✅ Automated Emails - Welcome message with pass attachment ✅ Spreadsheet Logging - Automatic record-keeping in Google Sheets ✅ Error Handling - Proper 400 responses for invalid signups ✅ Success Responses - Detailed JSON with all pass information Use Cases Gyms & Fitness Centers** - Trial pass management for new members Yoga Studios** - Week-long trial class passes Sports Clubs** - Guest pass generation with photo verification Wellness Centers** - Temporary access cards for trial periods Co-working Spaces** - Day pass generation with member photos Swimming Pools** - Verified trial memberships with photo IDs What You Need Required Credentials VerifiEmail API - Email verification service Get API key: https://verifi.email HTMLCSSToImage API - PNG image generation Get credentials: https://htmlcsstoimg.com HTMLCSSToPDF API - PDF conversion Get credentials: https://pdfmunk.com Gmail OAuth2 - Email delivery Connect your Google account Enable Gmail API in Google Cloud Console Google Sheets API - Data logging Connect your Google account Same OAuth2 as Gmail Setup Instructions Step 1: Create Google Sheet Create a new Google Sheet named "Gym Trial Passes 2025" Add these column headers in Row 1: Pass ID Name Email Start Date Valid Till Issued At Email Verified Status Step 2: Configure Credentials Add VerifiEmail API credentials Add HTMLCSSToImage credentials Add HTMLCSSToPDF credentials Connect Gmail OAuth2 Connect Google Sheets OAuth2 Step 3: Update Google Sheets Node Open "Log to Google Sheets" node Select your "Gym Trial Passes 2025" sheet Confirm column mappings match your headers Step 4: Test the Workflow Copy the webhook URL from the Webhook node Open Postman and create a POST request Use this test payload: { "name": "Rahul Sharma", "email": "your-email@gmail.com", "photo_url": "https://images.unsplash.com/photo-1633332755192-727a05c4013d?w=400", "start_date": "2025-11-15", "valid_till": "2025-11-22" } Send the request and check: ✅ Email received with PDF pass ✅ Google Sheet updated with new row ✅ Success JSON response returned Step 5: Activate & Use Click "Active" toggle to enable the workflow Integrate webhook URL with your gym's website form Members receive instant verified passes upon signup Expected Responses ✅ Success Response (200 OK) { "status": "success", "message": "Gym trial pass verified and sent successfully! 🎉", "data": { "pass_id": "GYM-1731398400123", "email": "member@example.com", "name": "Rahul Sharma", "valid_from": "November 15, 2025", "valid_till": "November 22, 2025", "email_verified": true, "recorded_in_sheets": true, "pass_sent_to_email": true }, "timestamp": "2025-11-12T10:30:45.123Z" } ❌ Error Response (400 Bad Request) { "status": "error", "message": "Invalid or disposable email address. Please use a valid email to register.", "email_verified": false, "email_provided": "test@tempmail.com" } Customization Options Modify Pass Design Edit the Build HTML Pass node to customize: Colors and gradient (currently purple gradient) Layout and spacing Fonts and typography Logo placement (add your gym logo) Additional branding elements Change Email Template Edit the Send Email with Pass node to modify: Subject line Welcome message Instructions Branding elements Footer content Adjust Validity Period Workflow accepts custom start_date and valid_till from webhook payload. You can also hardcode validity periods in the Generate Pass Details node. Add Additional Fields Extend the workflow to capture: Phone number Emergency contact Medical conditions Membership preferences Referral source Performance Average execution time**: 8-12 seconds Handles**: 100+ passes per hour PDF size**: ~150-250 KB Email delivery**: Instant (Gmail API) Success rate**: 99%+ with valid emails Security & Privacy ✅ Email verification prevents fake signups ✅ Unique Pass IDs prevent duplication ✅ All data logged in your private Google Sheet ✅ No data stored in n8n (passes through only) ✅ HTTPS webhook for secure data transmission ✅ OAuth2 authentication for Google services Tags gym fitness trial-pass email-verification qr-code pdf-generation member-onboarding automation verification photo-id

Who Is This For? This n8n automation workflow is designed for sales teams, client managers, consultants, or anyone who regularly schedules and follows up on meetings — and wants to save time doing it. If you often find yourself juggling between Google Sheets, Google Calendar, email, and WhatsApp just to manage your meetings, confirmations, and follow-ups — this workflow is for you. What This Workflow Does This workflow is structured into two main, independently scheduled branches: 1. Create Event (Schedule Meetings) Trigger:** Starts automatically on a schedule (e.g., every minute). Data Source:* Fetches new meeting data from a *Google Sheet**. Event Creation:* Creates a new event in *Google Calendar** using the data. Confirmation:* Sends a confirmation message via *WhatsApp (Rapiwa)* and *Email (Gmail)**. Status Update:* Updates the source *Google Sheet** to mark the meeting as 'sent'. 2. Reminder Event (Schedule Follow-ups) Trigger:** Starts automatically on a schedule (e.g., every minute). Past Events:* Retrieves recent past events from *Google Calendar**. Deduplication:** Uses a "Mark as Seen" node to prevent processing the same event multiple times. Filtering:** Filters for specific events that require a follow-up ("Only Follow Ups" node). AI Follow-up:* An *AI Meeting Agent (using Gemini/LLM)* uses the details of the past meeting and the Calendar's *Availability** tool to find and suggest open slots for a future meeting. Communication:* Sends a message with the suggested slots via *WhatsApp (Rapiwa)* and *Email (Gmail)**. Key Features Scheduled Automation:** Both event creation and follow-up scheduling run on a recurring schedule. Data Synchronization:* Reads meeting details from and updates a *Google Sheet**. Google Calendar Integration:** Creates events and checks calendar availability. Multi-Channel Communication:* Sends confirmations/follow-ups via *WhatsApp (Rapiwa)* and *Email (Gmail)**. AI-Powered Follow-up:* Uses an *AI Agent (Gemini)** to intelligently find and format available slots for the next meeting, considering the details of the past meeting (day, time, duration). Idempotency:** The "Mark as Seen" node prevents duplicate follow-up attempts for the same event. Requirements n8n instance with nodes: Schedule Trigger, Google Sheets, Split In Batches, Date & Time, Code, Google Calendar, Rapiwa, Gmail, Filter, Agent (LangChain), LLM Chat (Google Gemini), Structured Output Parser (LangChain), Set, Remove Duplicates, Wait. Google Calendar** with an available calendar for event creation and availability checks. Google Sheets** for storing meeting details. Rapiwa** (WhatsApp API) account credentials. Gmail** account credentials. Google Gemini (PaLM) API** credentials for the AI agent. How to Use — Step-by-Step Setup Credentials Setup Google Sheets OAuth2: Configure to allow the workflow to read from and write to your Sheet. Google Calendar OAuth2: Configure to allow event creation and availability checks. Rapiwa API: Set up credentials for sending WhatsApp messages. Gmail OAuth2: Set up credentials for sending email confirmations/follow-ups. Google Gemini(PaLM) API: Set up credentials for the AI agent functionality. Configure "Create Event" Branch Get in sheet: Update the Document ID and Sheet Name to point to your meeting data spreadsheet. The node is set to filter by a status column. Create an event: Verify the correct Calendar ID is selected. The end time is dynamically generated by the previous Code node. Rapiwa / Send a message1: Update the recipient number/email address and customize the message templates. Update status in sheet: Ensure the correct Document ID, Sheet Name, and matching column (row\_number) are configured to update the status to "sent". Configure "Reminder Event" Branch Get Past Events: Verify the correct Calendar ID is selected. Only Follow Ups: Customize the filter condition if only a subset of past meetings needs follow-up (e.g., if you have a "Follow-up Status" column to check). Meeting Agent: Review the System Message to ensure the AI's logic for finding slots matches your business rules (e.g., preferred working hours, look-ahead period). Generate Message: Customize the message template, which formats the AI-suggested slots. Rapiwa1 / Send a message: Update the recipient number/email address for the follow-up messages. Google Sheet Required Columns The workflow expects a Google Sheet with meeting data to have at least the following columns: A Google Sheet formatted like this ➤ Sample Sheet | title | description | location | color_number | start time | end time | reminder status | status | | :-------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------------- | :----------- | :----------------- | :----------------- | :-------------- | :------ | | 2025 Personal Planner & Events Calendar | Stay organized and never miss an important date! This calendar helps........ | Dhaka, Bangladesh | 4 | 10/28/2025 3:50:00 | 10/29/2025 5:30:00 | sent | checked | | 2026 Personal Planner & Events Calendar | Stay organized and never miss an important date! This calendar helps........ | Dhaka, Bangladesh | 2 | 10/29/2025 3:50:00 | 10/30/2025 5:30:00 | sent | checked | Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support & Help WhatsApp**: Chat on WhatsApp Discord**: SpaGreen Community Facebook Group**: SpaGreen Support Website**: https://spagreen.net Developer Portfolio**: Codecanyon SpaGreen

Wikipedia to LinkedIn AI Content Poster with Image via Bright Data 📋 Overview Workflow Description: Automatically scrapes Wikipedia articles, generates AI-powered LinkedIn summaries with custom images, and posts professional content to LinkedIn using Bright Data extraction and intelligent content optimization. 🚀 How It Works The workflow follows these simple steps: Article Input: User submits a Wikipedia article name through a simple form interface Data Extraction: Bright Data scrapes the Wikipedia article content including title and full text AI Summarization: Advanced AI models (OpenAI GPT-4 or Claude) create professional LinkedIn-optimized summaries under 2000 characters Image Generation: Ideogram AI creates relevant visual content based on the article summary LinkedIn Publishing: Automatically posts the summary with generated image to your LinkedIn profile URL Generation: Provides a shareable LinkedIn post URL for easy access and sharing ⚡ Setup Requirements Estimated Setup Time: 10-15 minutes Prerequisites n8n instance (self-hosted or cloud) Bright Data account with Wikipedia dataset access OpenAI API account (for GPT-4 access) Anthropic API account (for Claude access - optional) Ideogram AI account (for image generation) LinkedIn account with API access 🔧 Configuration Steps Step 1: Import Workflow Copy the provided JSON workflow file In n8n: Navigate to Workflows → + Add workflow → Import from JSON Paste the JSON content and click Import Save the workflow with a descriptive name Step 2: Configure API Credentials 🌐 Bright Data Setup Go to Credentials → + Add credential → Bright Data API Enter your Bright Data API token Replace BRIGHT_DATA_API_KEY in all HTTP request nodes Test the connection to ensure access 🤖 OpenAI Setup Configure OpenAI credentials in n8n Ensure GPT-4 model access Link credentials to the "OpenAI Chat Model" node Test API connectivity 🎨 Ideogram AI Setup Obtain Ideogram AI API key Replace IDEOGRAM_API_KEY in the "Image Generate" node Configure image generation parameters Test image generation functionality 💼 LinkedIn Setup Set up LinkedIn OAuth2 credentials in n8n Replace LINKEDIN_PROFILE_ID with your profile ID Configure posting permissions Test posting functionality Step 3: Configure Workflow Parameters Update Node Settings: Form Trigger:** Customize the form title and field labels as needed AI Agent:** Adjust the system message for different content styles Image Generate:** Modify image resolution and rendering speed settings LinkedIn Post:** Configure additional fields like hashtags or mentions Step 4: Test the Workflow Testing Recommendations: Start with a simple Wikipedia article (e.g., "Artificial Intelligence") Monitor each node execution for errors Verify the generated summary quality Check image generation and LinkedIn posting Confirm the final LinkedIn URL generation 🎯 Usage Instructions Running the Workflow Access the Form: Use the generated webhook URL to access the submission form Enter Article Name: Type the exact Wikipedia article title you want to process Submit Request: Click submit to start the automated process Monitor Progress: Check the n8n execution log for real-time progress View Results: The workflow will return a LinkedIn post URL upon completion Expected Output 📝 Content Summary Professional LinkedIn-optimized text Under 2000 characters Engaging and informative tone Bullet points for readability 🖼️ Generated Image High-quality AI-generated visual 1280x704 resolution Relevant to article content Professional appearance 🔗 LinkedIn Post Published to your LinkedIn profile Includes both text and image Shareable public URL Professional formatting 🛠️ Customization Options Content Personalization AI Prompts:** Modify the system message in the AI Agent node to change writing style Character Limits:** Adjust summary length requirements Tone Settings:** Change from professional to casual or technical Hashtag Integration:** Add relevant hashtags to LinkedIn posts Visual Customization Image Style:** Modify Ideogram prompts for different visual styles Resolution:** Change image dimensions based on LinkedIn requirements Rendering Speed:** Balance between speed and quality Brand Elements:** Include company logos or brand colors 🔍 Troubleshooting Common Issues & Solutions ⚠️ Bright Data Connection Issues Verify API key is correctly configured Check dataset access permissions Ensure sufficient API credits Validate Wikipedia article exists 🤖 AI Processing Errors Check OpenAI API quotas and limits Verify model access permissions Review input text length and format Test with simpler article content 🖼️ Image Generation Failures Validate Ideogram API key Check image prompt content Verify API usage limits Test with shorter prompts 💼 LinkedIn Posting Issues Re-authenticate LinkedIn OAuth Check posting permissions Verify profile ID configuration Test with shorter content ⚡ Performance & Limitations Expected Processing Times Wikipedia Scraping:** 30-60 seconds AI Summarization:** 15-30 seconds Image Generation:** 45-90 seconds LinkedIn Posting:** 10-15 seconds Total Workflow:** 2-4 minutes per article Usage Recommendations Best Practices: Use well-known Wikipedia articles for better results Monitor API usage across all services Test content quality before bulk processing Respect LinkedIn posting frequency limits Keep backup of successful configurations 📊 Use Cases 📚 Educational Content Create engaging educational posts from Wikipedia articles on science, history, or technology topics. 🏢 Thought Leadership Transform complex topics into accessible LinkedIn content to establish industry expertise. 📰 Content Marketing Generate regular, informative posts to maintain active LinkedIn presence with minimal effort. 🔬 Research Sharing Quickly summarize and share research findings or scientific discoveries with your network. 🎉 Conclusion This workflow provides a powerful, automated solution for creating professional LinkedIn content from Wikipedia articles. By combining web scraping, AI summarization, image generation, and social media posting, you can maintain an active and engaging LinkedIn presence with minimal manual effort. The workflow is designed to be flexible and customizable, allowing you to adapt the content style, visual elements, and posting frequency to match your professional brand and audience preferences. For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/

This workflow automatically notifies travelers about their pending trip payments and provides secure payment links through Email and WhatsApp. It runs twice daily (at 7 AM and 7 PM) to ensure timely reminders before the due date. Designed for travel agencies, it simplifies payment tracking, reduces manual follow-up, and ensures every traveler receives personalized reminders with real-time payment status updates. 🔧 Main Components Daily Payment Check – 7 AM & 7 PM Scheduled triggers that start the workflow daily at 7 AM and 7 PM. Read Pending Travel Payment Fetches traveler payment records from an Excel sheet (using getAll method). Process Payment Reminders Filters records to find pending payments due within the next 3 days. Create Payment Reminders Generates personalized payment reminders. Make Reminder For Email Prepares email-friendly messages with payment links. Send Email Reminder Sends the payment reminder email with a secure payment link to the traveler. Prepare WhatsApp Reminder Generates WhatsApp-friendly messages with payment and payment details. Send WhatsApp Message Sends the message to the traveler’s WhatsApp number using a message API. Update Status Of Reminder Updates the Excel file to mark reminders as sent to avoid duplicates. 🧩 Channels Used 📧 Email – with personalized payment link 💬 WhatsApp – formatted reminder message 🔐 Payment Integration Secure payment links are auto-generated per traveler to enable direct and safe online payments. ✅ Essential Prerequisites Excel sheet with payment records (travel_payment_data.xlsx) SMTP credentials for sending email WhatsApp API or provider integration (like Twilio or Gupshup) Access to a payment gateway or service for link generation File storage access to update reminder status in Excel 📁 Required Excel File Structure (travel_payment_data.xlsx) | Traveler ID | Name | Email | Phone | Payment Due Date | Amount | Reminder Sent | |-------------|------------|-------------------|---------------|------------------|---------|---------------| | TR001 | Arjun Patel| arjun@example.com | +919876543210 | 2025-10-20 | ₹3000 | No | 🧾 Expected Input Format Example { "travelerId": "TR001", "name": "Arjun Patel", "email": "arjun@example.com", "phone": "+919876543210", "dueDate": "2025-10-20", "amount": "₹3000", "reminderSent": "No" } 🚀 Key Features ⏰ Scheduled Daily Execution – Fully automated at 7 AM and 7 PM 🧮 Due-Date Filtering – Only targets payments due in the next 3 days 💬 Multi-Channel Notifications – Sends reminders via both Email and WhatsApp 🔗 Secure Payment Links – Auto-generated for each traveler 🔄 Reminder Tracking – Prevents duplicate reminders by updating status ⚙️ Quick Setup Guide Import Workflow JSON into your n8n instance. Configure schedule in the “Daily Payment Check” node (default: 7 AM & 7 PM). Set Excel file path in the “Read Pending Travel Payment” node. Update your payment processing logic in the “Process Payment Reminders” node. Add email credentials in the “Send Email Reminder” node. Integrate WhatsApp provider API in the “Send WhatsApp Message” node. Define how you generate secure payment links. Test with sample data and activate workflow.