Workflow Templates

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

Analyze YouTube videos for virality with an AI-powered report This workflow automates the discovery and analysis of potentially viral YouTube videos. It searches for recent, popular videos based on a keyword, calculates a unique "Algorithmic Lift Score" to measure virality, and uses an AI agent to generate an insightful summary report that is sent directly to your email. What it does This workflow identifies videos that are outperforming their channel's baseline, a key indicator of viral potential. It operates in several stages: Searches YouTube: It finds recent, top-performing videos based on your specified keyword and timeframe. Gathers Data: For each video found, it fetches detailed statistics for both the video (views, likes, comments) and its channel (subscriber count, total views). Calculates Virality Score: It calculates an "Algorithmic Lift Score" for each video. This custom metric prioritizes videos that achieve high view counts and engagement relative to their channel's subscriber base. Analyzes with AI: The top 5 videos, sorted by their virality score, are sent to an AI agent (pre-configured for OpenAI). The AI generates a concise summary highlighting trends, top performers, and other noteworthy patterns. Sends Email Report: The final AI-generated analysis is converted to HTML and emailed to you, providing a ready-to-read report on what's trending in your niche. Who it's for This workflow is perfect for: Content Creators** looking for trending topics and content ideas. Digital Marketers** conducting competitor analysis or market research. Social Media Managers** wanting to understand what content resonates on YouTube. Data Analysts** who need to automate the collection and analysis of YouTube trends. Requirements A Google API Key with the "YouTube Data API v3" enabled. An OpenAI API Key (or another compatible AI model credential). A connected Gmail account in n8n to send the final report. How to set up Configure the Setup Node: Click on the "Setup" node and fill in the values: query: The keyword you want to search for (e.g., "AI tools"). GoogleAPIkey: Your Google API key. daysback: How many days in the past to search for new videos. maxResult: The number of videos to analyze (e.g., 20). email: The email address where the report will be sent. Set AI Credentials: Click the "OpenAI Chat Model" node and add your OpenAI API key to the credentials. Set Gmail Credentials: Click the "Send_Report" node and connect your Gmail account to the credentials.

LinkedIn URL → Scrape → Match → Screen → Decide, all automated This workflow automatically processes candidate LinkedIn profiles shared via Telegram, intelligently matches them to job descriptions, performs AI-powered screening analysis, and sends actionable summaries to your team in Telegram. Good to know Handles LinkedIn profile scraping via Apify API (extracts full profile data including experience, education, skills) Built-in spam prevention: limits users to 3 LinkedIn profile submissions Two-stage JD matching: prioritizes role mentioned in candidate's Telegram message, falls back to LinkedIn profile analysis if needed Uses Google Gemini API for AI screening (generous free tier and rate limits, typically enough to avoid paying for API requests - check latest pricing at Google AI Pricing and rate limits documentation) Automatic polling mechanism checks Apify extraction status up to 10 times (15-second intervals) Complete audit trail logged in Google Sheets with unique submission IDs Who's it for Hiring teams and recruiters who want to streamline first-round screening for candidates who share LinkedIn profiles directly. Perfect for companies accepting applications via messaging platforms (Telegram, WhatsApp, etc.), especially useful fortech-savvy audiences and remote/global hiring. How it works Telegram bot receives message containing LinkedIn profile URL from candidate Validates URL format and checks spam prevention (max 3 submissions per Telegram username) Sends confirmation message to candidate and notifies internal talent team via Telegram group Extracts clean LinkedIn URL and initiates Apify scraping job Polls Apify API up to 10 times (15-second intervals) until profile extraction completes AI agent matches candidate to best-fit job description by analyzing Telegram message context first (if candidate mentioned a role), or LinkedIn profile content as fallback (selects up to 3 potential JD matches) If multiple JDs matched, second AI agent selects the single best fit based on detailed profile analysis AI recruiter agent analyzes LinkedIn profile against selected JD and generates structured screening report (strengths, weaknesses, risk/reward factors, overall fit score 0-10 with justification) Logs complete analysis to Google Sheets tracker with unique submission ID Sends formatted summary to Telegram group with candidate details, matched JD, and overall fit score Requirements Telegram Bot Token (Create bot via @BotFather) Apify account with API token (Sign up for free tier) Google Drive account (OAuth2) Google Sheets account (OAuth2) Google Gemini API key (Get free key here) Google Drive folder for Job Descriptions (as PDFs or Google Docs) Telegram group for internal talent team notifications How to set up Create Telegram bot and internal Telegram chat group with new bot: Message @BotFather on Telegram Send /newbot and follow instructions to create your bot Save the API token provided Create Telegram group chat and invite your new bot + invite the @GetIDs bot Note down the group chat ID (How to get group chat ID) Setup Apify: Sign up at Apify Get your API token from Settings Note: Free tier includes sufficient scraping credits for testing and production ($0.01 per successful LinkedIn profile enriched, a free monthly limit of $5.00) - LinkedIn profile scraper "actor" details Create Google Sheet: Create new sheet named "LinkedIn Profile AI Candidate Screening" Add columns: Submission ID, Date, LinkedIn Profile URL, First Name, Last Name, Email (if known), Telegram Username, Strengths, Weaknesses, Risk Factor, Reward Factor, JD Match, Overall Fit, Justification Copy the spreadsheet ID from URL Setup Google Drive folder: Create folder named "Job Descriptions" Upload your JD files (PDFs or Google Docs) with clear, descriptive filenames Copy the folder ID from URL Configure workflow nodes: In "Receive Telegram Msg to Recruiter Bot" node: Add Telegram API credentials In "Extract LinkedIn Profile Information" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Check LinkedIn Profile Extraction Status" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Get Fully Extracted LinkedIn Profile Data" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Access JD Files" node: Update folder ID to your "Job Descriptions" folder In "Get All Rows Matching Telegram Username" node: Select your Google Sheet In "Add Candidate Analysis in GSheet" node: Select your Google Sheet and verify column mappings In "Send Msg to Internal Talent Group" node: Update chat ID to your Telegram group chat ID In "Send Review Completed Msg to Talent Group" node: Update chat ID and Google Sheet URL Add your company description: In "JD Matching Agent" system message: Replace company description with your details In "Detailed JD Matching Agent" system message: Replace company description with your details In "Recruiter Scoring Agent" system message: Update company description Test the workflow: Send a LinkedIn profile URL to your bot from Telegram Monitor execution to ensure all nodes run successfully Check Google Sheets for logged results Activate workflow Customizing this workflow Change spam limits: Edit "Spam Check: Sent <4 LinkedIn Profiles?" node to adjust maximum submissions (currently 3) Adjust polling attempts: Edit "Checked 10x for LinkedIn Profile Data?" node to change maximum polling attempts (currently 10) or modify wait time in "Wait for LinkedIn Profile" node (currently 15 seconds) Change JD matching logic: Edit "JD Matching Agent" node prompt to adjust how LinkedIn profiles are matched to roles (e.g., weight current role vs. overall experience) Modify screening criteria: Edit "Recruiter Scoring Agent" node system message to focus on specific qualities (culture fit, leadership potential, technical depth, industry experience, etc.) Add more messaging platforms: Add nodes to support WhatsApp, Discord, or other messaging platforms using similar URL-based triggers Customize Telegram messages: Edit notification nodes to change formatting, add emojis, or include additional candidate data Auto-proceed logic: Add IF node after screening to auto-proceed candidates with fit score above threshold (e.g., 8+/10) and trigger different notification paths Add candidate responses: Connect nodes to automatically message candidates back via Telegram (confirmation, rejection, interview invite) Add interview scheduling: For approved candidates, send Telegram message with Cal.com or Calendly link so they can book their interview Enrich with additional data: Add nodes to cross-reference candidate data with other sources (GitHub, Twitter/X, company websites) Multi-language support: Add translation nodes to support candidates submitting profiles in different languages Add human approval step: Create buttons in Telegram group messages for instant Approve/Reject decisions that update Google Sheets Pro tip: Add your Telegram bot to your company's careers page with instructions like: "Want fast-track screening? Share your LinkedIn profile with our AI recruiter: @YourBotName" Troubleshooting Telegram bot not responding: Ensure bot token is correct in "Receive Telegram Msg to Recruiter Bot" node, and users have sent /start to your bot at least once "LinkedIn profile URL invalid" error: Check that candidates are sending full URLs in format https://www.linkedin.com/in/username (not shortened links or text without URL) Apify extraction failing: Verify Apify API token is correctly set in all three HTTP Request nodes ("Extract LinkedIn Profile Information", "Check LinkedIn Profile Extraction Status", "Get Fully Extracted LinkedIn Profile Data") LinkedIn extraction timeout: Increase polling attempts in "Checked 10x for LinkedIn Profile Data?" node (currently 10) or increase wait time in "Wait for LinkedIn Profile" node (currently 15 seconds) Spam check blocking valid users: Check "Get All Rows Matching Telegram Username" node is pointing to correct Google Sheet, and adjust limit in "Spam Check: Sent <4 LinkedIn Profiles?" node if needed JD matching returns no results: Check "Access JD Files" node folder ID points to your Job Descriptions folder, and JD files are named clearly (e.g., "Marketing Director JD.pdf") JD matching is not relevant for my company: Update the "Company Description" in the System Messages in all three AI agent nodes ("JD Matching Agent", "Detailed JD Matching Agent", "Recruiter Scoring Agent") "Can't find matching JD": Ensure candidate's Telegram message mentions role name OR their LinkedIn profile clearly indicates relevant experience for available JDs Google Sheets errors: Verify sheet name is "LinkedIn Profile AI Candidate Screening" and column headers exactly match workflow expectations (Submission ID, Date, LinkedIn Profile URL, First Name, Last Name, etc.) Telegram group notifications not appearing: Verify chat ID is correct in "Send Msg to Internal Talent Group" and "Send Review Completed Msg to Talent Group" nodes (use negative number for group chats, e.g., -4954246611) Missing candidate data in Google Sheets: LinkedIn profile may be incomplete - verify Apify successfully extracted data by checking "Get Fully Extracted LinkedIn Profile Data" node output Loop counter not working: Check "Restore Loop Counter" code node references correct node names ("Checked 10x for LinkedIn Profile Data?" and "Initialize Loop Counter to Poll for Completion") 401/403 API errors: Re-authorize all OAuth2 credentials (Google Drive, Google Sheets) and verify Apify and Telegram API tokens are valid AI analysis quality issues: Edit system prompts in "JD Matching Agent", "Detailed JD Matching Agent", and "Recruiter Scoring Agent" nodes to refine screening criteria and provide more context about your hiring needs Gemini API rate limit errors: Check your usage at Google AI Studio and consider upgrading to paid tier if exceeding free tier limits (see rate limits documentation) Sample Outputs Google Sheets - LinkedIn AI Candidate Screening - sample Telegram messages between AI recruiter bot and job applicant Telegram messages from AI recruiter bot in internal group chat

How it works Automatically generates professional PDF invoices from webhook data and delivers them via email while storing backups in Google Drive. Perfect for freelancers, small businesses, and service providers who need automated billing workflows. Set up steps Configure environment variables for company information (name, address, email, phone). Set up your PDF generation API service account (PDFShift recommended). Configure SMTP email credentials for invoice delivery. Set up Google Drive OAuth2 for cloud storage. Deploy the workflow and test with sample invoice data. Key features Smart invoice number generation if not provided Automatic tax calculations with configurable rates Professional HTML templates with company branding Parallel processing for email and storage Comprehensive error handling and validation Detailed success confirmation responses Required environment variables COMPANY_NAME - Your business name COMPANY_ADDRESS - Business mailing address COMPANY_EMAIL - Billing contact email COMPANY_PHONE - Business phone number PDF_API_URL - PDF generation service endpoint PDF_API_KEY - API authentication key GDRIVE_INVOICE_FOLDER_ID - Google Drive folder ID API requirements PDF generation service (PDFShift, HTML/CSS to PDF API, or similar), SMTP email service for delivery, Google Drive API access for storage. Input format { "customerName": "John Smith", "customerEmail": "john@example.com", "items": [ {"description": "Web Design", "quantity": 1, "price": 500} ], "dueDate": "2025-02-15" }

Overview Automate your personal productivity with this intelligent n8n workflow that integrates Telegram, Google Sheets, and OpenAI (GPT-4o). This system uses multiple AI agents to manage work hours, tasks, finances, and emails—all through natural language commands sent via Telegram. Every action is synced to Google Sheets for persistent, structured data storage. What This Template Does This automation system deploys several specialized AI agents: 📊 Work Hours Analyzer**: Analyzes work logs from Google Sheets, calculates total hours by workplace, and generates detailed monthly reports in Arabic. 🛠️ Work Tracking Agent**: Handles start/end work commands, calculates total hours, and updates Google Sheets. 📋 Task Manager Agent**: Manages to-do lists—adding, listing, updating, completing, and deleting tasks—with real-time sync to Google Sheets. 💰 Finance Agent**: Tracks income and expenses in multiple currencies, summarizes daily financial activity, and maintains a full transaction history. 📧 Email Analysis Agent**: Processes incoming Gmail messages, generates AI-powered summaries in Arabic with priority, sentiment, and recommended actions. 📅 Monthly Report Generator**: Automatically triggers at the start of each month to compile a professional PDF report of work hours and sends it to a Telegram topic. Prerequisites & Setup Required Accounts & API Keys Before setup, ensure you have: Telegram Bot Token – from @BotFather OpenAI API Key – with access to gpt-4o-mini or gpt-3.5-turbo Google Sheets API – OAuth2 credentials enabled Gmail Account (Optional) – for email analysis n8n Instance – self-hosted or cloud Google Sheets Structure Create a Google Sheet with the following sheets and columns: Sheet: work Date start at end at place note Total hours Sheet: task Task Status Created At Due Date Notes Sheet: Expenses id Amount Currency Note Type (debit/credit) Date Time Sheet: email name email Step-by-Step Setup Step 1: Import the Workflow In n8n, go to Workflows > Import from file Upload the JSON template Open the canvas and verify all nodes are connected Step 2: Configure Credentials Telegram: Add your bot token under "Telegram account" OpenAI: Enter your API key in "OpenAi account" Google Sheets: Connect using OAuth2 under "Google Sheets account" Gmail (Optional): Set up if using email analysis Step 3: Link Google Sheets Share your Google Sheet with the service account email (if using service account) Copy the Document ID from the sheet URL Update all Google Sheets nodes with the correct sheet names and IDs Ensure column names match exactly Step 4: Set Up Telegram Start a chat with your bot Use /start to initialize Ensure chatId and message_thread_id in Telegram nodes match your group/topic Test sending a message like "Start work at the factory" Step 5: Test the Agents Try these sample commands via Telegram: "Start work at the factory" → Logs start time "Finished work" → Logs end time and calculates hours "Add task: pay the bill" → Adds a new task "How much did I spend today?" → Shows today’s expenses "Send last month's report" → Triggers monthly PDF report (on the first of the month) Key Features Smart Work Tracking Automatic time calculation Query by date, place, or period Real-time Google Sheets sync Task Management Add, list, update, complete, delete tasks Friendly, conversational responses Daily summaries of completed and upcoming tasks Financial Tracking Supports multiple currencies (JOD, USD, ILS, etc.) Daily income/expense summaries Full transaction history Arabic-language responses Email Intelligence AI-powered email summaries Priority, sentiment, and action recommendations Plain-text output in Arabic No JSON or code blocks Automated Monthly Reports Triggered on the 1st of each month Generates detailed work hour reports by workplace Outputs clean, formatted PDF Sends directly to Telegram topic Customization Options Modify AI Prompts Edit the systemMessage in any AI agent node to: Change tone (formal, friendly, concise) Add new response formats Support additional commands or languages Extend Functionality Add daily reminders using Schedule Trigger Implement budget alerts when expenses exceed a threshold Add weekly summaries for tasks or work hours Support multi-currency conversion Enhance Telegram Interaction Add inline buttons for quick actions Create shortcuts like /work, /tasks, /finance Use message_thread_id to organize topics Troubleshooting | Issue | Solution | |------|----------| | Bot not responding | Check webhook URL, bot token, and chatId | | Google Sheets not updating | Verify OAuth2 permissions and sheet sharing | | AI not understanding commands | Review prompt clarity and test input phrasing | | Monthly report not sending | Confirm Schedule Trigger timezone and execution time | Benefits ✅ Full automation with minimal user input 📱 Control everything from Telegram 📊 Data stored securely in Google Sheets 📄 Professional PDF reports generated automatically 💬 Natural, friendly Arabic responses 🔁 Seamless sync across all components This template transforms personal productivity by combining AI intelligence with powerful automation—turning simple Telegram messages into structured data, actionable insights, and professional reports.

Description Automatically qualify and route new leads from a Google Sheet into your CRM with AI-powered scoring and instant sales notifications. Turn raw form submissions into prioritized opportunities—effortlessly. ⚡ What This Template Does Monitors a Google Sheet for new form submissions. 📄 Uses Azure OpenAI (GPT-4o-mini) to analyze lead details (value, stage, company) and generate action items. 🤖 Parses the AI response into clean JSON for structured processing. 🗂️ Saves qualified lead data and AI-generated action items into a Lead Status sheet for tracking. 💾 Categorizes leads into Hot, Warm, or Cold based on AI scoring. 🔥❄️ Creates/updates the contact in HighLevel CRM. 📇 Sends an email notification to the assigned sales rep with lead details and priority. 📧 Key Benefits Save time with automated lead qualification instead of manual checks. ⏱️ Ensure consistent Hot/Warm/Cold scoring across all leads. ✅ Centralize lead data in both Google Sheets and CRM for tracking. 📊 Keep sales teams aligned with instant notifications. 🚀 Fully no-code configurable and customizable for your business logic. 🧩 Features Google Sheets Trigger for new form rows. 📥 AI Agent with Azure OpenAI (GPT-4o-mini) for lead scoring. 🧠 JSON parsing node to clean AI output. ✂️ Lead logging to “Lead Status” sheet. 📊 Function node to categorize leads by score. 🎯 CRM sync with HighLevel to update/create contact records. 🔗 SMTP email notification to sales reps. ✉️ Requirements n8n instance (cloud or self-hosted). 🧰 Google Sheet with headers: Lead Name, Lead Email, Lead Contact No., Company Name, Opportunity Value, Stage of Lead; shared with n8n Google account. 📑 Azure OpenAI access with a GPT-4o-mini deployment. ☁️ HighLevel CRM account connected via OAuth. 📇 SMTP email account configured in n8n. 📧 Target Audience Sales teams handling inbound leads. 📈 Agencies managing multiple client pipelines. 🤝 Founders/startups wanting quick qualification and CRM sync. 🚀 Ops teams needing reliable reporting of lead qualification. 🗂️ Step-by-Step Setup Instructions (Concise) Create a Google Sheet with required headers; share with n8n account. 📋 Configure the Google Sheets Trigger with the sheet’s Document ID. 🔐 Connect your Azure OpenAI credentials and link to the AI Agent node. 🧠 Assign your HighLevel CRM account credentials. 📇 Set up SMTP credentials for the email send node. ✉️ Import the workflow, update node configs, and run a test submission. ▶️ Security Best Practices Share Google Sheets only with the n8n Google account (Editor). 🔒 Keep API keys and credentials encrypted in n8n, not hardcoded. 🛡️ Validate AI outputs before saving to CRM (via the parse node). ✅ Regularly back up your Lead Status sheet and CRM data. 📂

Automated Solana News Tracker with AI-Powered Weekly Summaries Never miss important Solana ecosystem updates again. This production-ready workflow automatically scrapes crypto news daily, intelligently filters duplicates, stores everything in Google Sheets, and generates AI-powered weekly summaries every Monday—completely hands-free. 🎯 What It Does: This intelligent automation runs on autopilot to keep you informed about Solana developments without manual monitoring. Every day at 8 AM PT, it fetches the latest Solana news from CryptoPanic, checks for duplicates against your existing database, and stores only new articles in Google Sheets. On Mondays, it takes an extra step: reading all accumulated articles from the past week and using GPT-4.1-mini to generate a concise, factual summary of key developments and investor takeaways. Daily News Collection**: Automatically fetches latest Solana articles from CryptoPanic API Smart Duplicate Detection**: Compares incoming articles against existing database to prevent redundancy Data Validation**: Filters out incomplete articles to ensure data quality Organized Storage**: Maintains clean Google Sheets database with timestamps and descriptions Weekly AI Summaries**: Analyzes accumulated news every Monday and generates 2-3 sentence insights Historical Archive**: Builds searchable database of both raw articles and weekly summaries 💼 Perfect For: Crypto traders tracking market-moving news • SOL investors monitoring ecosystem growth • Blockchain researchers building historical datasets • Content creators sourcing newsletter material • Portfolio managers needing daily briefings • Anyone wanting Solana updates without information overload 🔧 How It Works: The workflow operates in two distinct modes based on the day of the week. During the daily collection phase (Tuesday-Sunday), it runs at 8 AM PT, fetches the latest Solana news from CryptoPanic, formats the data to extract titles, descriptions, and timestamps, checks each article against your Google Sheets database to identify duplicates, filters out any articles that already exist or have missing data, and appends only valid new articles to your "Raw Data" sheet. On Mondays, the workflow performs all daily tasks plus an additional summarization step. After storing new articles, it retrieves all accumulated news from the "Raw Data" sheet, aggregates all article descriptions into a single text block, sends this consolidated information to GPT-4.1-mini with instructions to create a factual, spartan-toned summary highlighting key investor takeaways, and saves the AI-generated summary with a timestamp to the "Weekly Summary" sheet for historical reference. ✨ Key Features: Schedule-based execution**: Runs automatically at 8 AM PT every day without manual intervention Intelligent deduplication**: Title-based matching prevents storing the same article multiple times Data quality control**: Validates required fields before storage to maintain clean dataset Dual-sheet architecture**: Separate sheets for raw articles and weekly summaries for easy access Cost-effective AI**: Uses GPT-4.1-mini (~$0.001 per summary) for extremely low operating costs Scalable storage**: Google Sheets handles thousands of articles with free tier Customizable cryptocurrency**: Easily adapt to track Bitcoin, Ethereum, or any supported coin Flexible scheduling**: Modify trigger time and summary frequency to match your needs 📋 Requirements: CryptoPanic account with free API key (register at cryptopanic.com) Google Sheets with two sheets: "Raw Data" (columns: date, title, descripton, summary) and "Weekly Summary" (columns: Date, Summary) OpenAI API key for GPT-4.1-mini access (~$0.05/month cost) n8n Cloud or self-hosted instance with schedule trigger enabled ⚡ Quick Setup: Register for a free CryptoPanic API key and replace [your token] in the "Get Solana News" HTTP Request node URL. Create a new Google Spreadsheet with two sheets: one named "Raw Data" with columns for date, title, descripton (note the typo in template), and summary; another named "Weekly Summary" with columns for Date and Summary. Connect your Google Sheets OAuth2 credential to all Google Sheets nodes in the workflow. Add your OpenAI API credential to the "Summarize News" node. Test the workflow manually to ensure it fetches news and stores it correctly. Activate the workflow to enable daily automatic execution. 🚨 Please note, that you're not able to get news in real-time with a FREE CryptoPanic API. Consider their pro plan or another platform for real-time news scraping You'll get new that's up to date as of yesterday. 🎁 What You Get: Complete end-to-end automation with concise sticky note documentation at each workflow stage, pre-configured duplicate detection logic, AI summarization with investor-focused prompts optimized for factual analysis without hype, dual-sheet Google Sheets structure for raw data and summaries, flexible schedule trigger you can adjust to any timezone, example data in pinned format showing expected API responses, customization guides for different cryptocurrencies and summary frequencies, and troubleshooting checklist for common setup issues. 💰 Expected Costs & Performance: CryptoPanic API is free with reasonable rate limits for personal use. OpenAI GPT-4.1-mini costs approximately $0.001 per summary, totaling about $0.05 per month for weekly summaries. The workflow typically processes 20-50 articles daily and generates one summary weekly from 140-350 accumulated articles. Daily executions complete in 5-10 seconds, while Monday runs with AI summarization take 15-20 seconds. Google Sheets provides free storage for up to 5 million cells, easily handling years of news data. 🔄 Customization Ideas: Track different cryptocurrencies by changing the currencies parameter (btc, eth, ada, doge, etc.). Adjust the schedule trigger to run at different times matching your timezone. Modify the Monday check condition to generate summaries on different days or multiple times per week. Connect Slack, Discord, or Email nodes to receive instant notifications when summaries are generated. Edit the AI prompt to change tone, detail level, or focus on specific aspects like price action, development updates, or partnerships. Add conditional logic to send alerts only when certain keywords appear in news (like "hack," "partnership," or "upgrade").

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.

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.

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.

📄 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.

This workflow is an autonomous AI research assistant that transforms a single topic into a comprehensive, multi-chapter report. Designed for researchers, students, and content creators, it automates the entire process from planning and online research to writing, formatting, and delivering a final PDF report directly to your email. How it works Trigger: The workflow begins when a user submits a research topic and an email address through a form. AI Planning: An AI agent breaks the main topic into five focused subtopics. It then generates an engaging report title, a detailed introduction, and chapter headings, saving this initial structure to a Google Sheet. Parallel Research and Writing: The workflow then splits into five parallel paths, one for each subtopic. In each path, it uses the Tavily Search API to gather real-time information from the web. A dedicated AI writer then synthesizes this research into a complete, well-formatted HTML chapter with inline citations. Content Aggregation: As each chapter is completed, its content, sources, and section titles are saved to the central Google Sheet. Final Assembly and Delivery: Once all chapters are written, the workflow compiles the title, introduction, a newly generated table of contents, all chapters, and a complete list of sources into a single HTML document. This document is sent to APITemplate.io to be converted into a professionally formatted PDF, which is then emailed as an attachment to the address provided in the form. Set up steps Google Sheets: Make a copy of the provided Google Sheet Template. Connect your Google account in the credentials menu. Update all Google Sheets nodes to use your copied sheet by selecting it from the list. AI Language Model (Google Gemini): Sign up for an API key from the Google AI Platform. Connect your account in the Google Gemini Chat Model nodes. This template is pre-configured for the affordable gemini-pro-flash-lite model. Tavily Search API: Sign up for a free account at Tavily and get an API key. In the Tavily HTTP Request nodes, create a new Header Auth credential. For the Name, enter X-Tavily-API-Key and for the Value, paste your Tavily API key. APITemplate.io: Sign up for a free account at APITemplate.io and get an API key. Connect your account in the Generate PDF node's credentials. Gmail: Connect the Gmail account you want to send the final report from in the Send Report node's credentials.