Workflow Templates

Research meeting attendees and prepare daily agenda in Slack This workflow automatically researches your meeting attendees every morning and sends you a comprehensive brief in Slack with context about who you're meeting, their company, and key talking points. Who's it for Sales professionals who need quick context before meetings Executives with packed calendars who need meeting preparation Customer success teams managing multiple client relationships Account managers preparing for client calls Business development teams researching prospects Anyone who wants to be better prepared for their daily meetings How it works Daily Trigger: Runs every weekday morning at 6 AM (customizable) to analyze your Google Calendar Calendar Analysis: Fetches all meetings scheduled for today and filters for external meetings (those with attendees other than yourself) AI-Powered Research: For each external meeting, an AI agent researches attendees using multiple sources: Searches your CRM (Attio) for existing contact information Queries Gmail history for past email interactions Searches past calendar events for previous meetings with attendees Performs web searches for recent news about attendees and their companies Retrieves company data from Apollo.io including industry, size, and technologies CRM Updates: Automatically creates new contact records in Attio for unknown attendees and adds meeting preparation notes to existing contacts Brief Generation: Compiles all research into a scannable, actionable meeting brief with key talking points Slack Delivery: Sends the formatted brief to your designated Slack channel for easy mobile access Setup requirements Google Calendar** OAuth2 connection (for fetching meetings) Slack** workspace with bot permissions (for receiving briefs) Gmail** OAuth2 connection (for email history search) OpenRouter** API key (for AI processing) Attio CRM** account and API token (optional - for contact management) Apollo.io** API key (optional - for company research) Anthropic** API key (optional - for advanced web search) How to customize Adjust Schedule: Modify the Schedule Trigger node to run at your preferred time - change from 6 AM to whenever works best for your schedule Customize Research Sources: Remove CRM integration if you don't use Attio Remove Apollo.io if you don't need company research Add additional research tools as needed Modify Output Format: Edit the prompt in "Format Daily Meeting Brief" node to change how the information is structured and presented Change Delivery Method: Replace Slack with Microsoft Teams, email, or Discord Add multiple delivery channels if needed Send to different channels based on meeting type Filter Meetings: Adjust the filtering logic to include/exclude certain types of meetings based on keywords, attendees, or calendar properties Advanced customization Add VIP alerts**: Create special handling for meetings with executives or key clients Include preparation documents**: Automatically attach relevant files from Google Drive Time zone handling**: Adjust for meetings across different time zones Language support**: Modify prompts to generate briefs in different languages

Automate Business Card Management with LINE, AI, and Google Sheets Who's it for This workflow is designed for business professionals and sales teams who receive business card images via LINE and want to quickly digitize contact information with minimal manual work. It is best suited for users who process business cards one image at a time and want a simple, reliable automation rather than a high-volume ingestion pipeline. What it does This workflow processes a single business card image sent via LINE, extracts text using Google Gemini AI, and stores the structured contact information in Google Sheets. The workflow focuses on simplicity and clarity: it receives an image, performs AI-based OCR, parses the extracted text, saves the result, uploads the original image for reference, sends a thank-you email, and replies with the extracted data on LINE. How it works A single business card image is sent to the LINE bot. The workflow is triggered via a LINE webhook. The image file is downloaded and sent to Google Gemini AI for OCR. The extracted text is parsed into structured fields. The data is appended to Google Sheets. The image is uploaded to Google Drive. A thank-you email is sent via Gmail. The extracted information is sent back as a LINE reply. This workflow is intentionally designed to handle one image per execution. Requirements To use this workflow, you will need: A LINE Messaging API account A Google Gemini API key A Google account with access to Google Sheets and Google Drive A Gmail account for sending thank-you emails A Google Sheets document with the following column names: Company Name Contact Name Department Address Email Address Phone Number Important limitations This workflow does not support multiple images sent in a single message. Sending images in quick succession may trigger multiple executions and lead to unexpected results. Only the first image in an event payload is processed. OCR accuracy depends on image quality, lighting, and card design. These limitations are intentional to keep the workflow simple and easy to understand. How to set up Create a LINE Messaging API channel and obtain a Channel Access Token. Generate a Google Gemini API key. Update the Config node with your LINE token, Google Sheets ID, and Google Drive folder ID. Configure credentials for LINE, Google Gemini, Google Sheets, Google Drive, and Gmail. Register the n8n webhook URL in your LINE channel settings. Activate the workflow in n8n and test it with a single business card image. How to customize Modify the AI prompt in the “Extract Card Info” node to support different languages or fields. Adjust the parsing logic to match different business card layouts. Replace Google Sheets with a CRM or database. Add queueing or locking logic if you want to support batch or sequential image uploads. Note: This workflow was tested using real business card images sent individually via the LINE Messaging API. For production use, testing with your own card samples is strongly recommended.

Classify YouTube Trends and Generate Email Summaries with GPT-4 and Gmail Monitor YouTube channels, fetch stats, classify videos as viral (≥ 1000 likes) or normal, and auto‑generate LinkedIn/email summaries with GPT‑4. Deliver via Gmail or SMTP. Clear node names, examples, and auditable fields. 🎯 Overview This template monitors YouTube channels via RSS or the YouTube Data API, retrieves video stats, classifies each video as viral (≥ 1000 likes) or normal, and produces concise LinkedIn/email summaries with OpenAI (GPT‑4 family). It can send a compact weekly briefing via Gmail (OAuth2) or SMTP. Built for creators, marketing teams, and agencies who want automated trend alerts and ready‑to‑use content. This screenshot shows the Gmail-ready weekly briefing generated by the Generate Weekly Briefing (HTML) node in my YouTube Trend Detector workflow, confirming the end-to-end pipeline: RSS/API → stats → like-based classification (≥ 1000 = viral) → LLM summaries → HTML email. 🧭 How It Works (Node Map) Manual Run – ad‑hoc execution Set Channel IDs – provide one or more YouTube channelId values Split Channels – process channels one by one Fetch Latest Videos (RSS) – pull recent uploads via channel RSS Filter: Published in Last 72h – only recent items are kept Get Video Stats (YouTube API) – request snippet,statistics for likes and details Classify by Likes (Code) – sets classification to viral or normal Branch: Normal / Branch: Viral – separate LLM prompts per relevance Write Post (Normal / Viral) – generate LinkedIn‑style notes via OpenAI Aggregate Posts for Briefing – merge all texts into one block Generate Weekly Briefing (HTML) – produce a Gmail‑robust HTML email via GPT Send Weekly Briefing (Gmail/SMTP) – deliver briefing (you set recipients) ⚙️ Quick Start (≈ 3 minutes) Import the sanitized JSON into n8n (Menu → Import). Create credentials (use exact names): YouTube_API_Key — Generic credential (field: apiKey) OpenAi account — OpenAI API Key Gmail account (OAuth2) or SMTP_Default (SMTP) Configure channels: In Set Channel IDs, list your YouTube channelId values (e.g., UC…). Set recipients: In Send Weekly Briefing, add your target email(s). Test: Run Execute Workflow and review outputs from the LLM and send nodes. 🔑 Required Credentials YouTube_API_Key** — YouTube Data API v3 key (field apiKey) OpenAi account** — OpenAI API key for LLM nodes Gmail account* (OAuth2, recommended) *or* *SMTP_Default** (server/port/TLS + app password if 2FA) 🧩 Key Parameters & Adjustments Viral threshold:** In Classify by Likes (Code) → const THRESHOLD = 1000; YouTube API parts:** Use part=snippet,statistics to obtain likeCount Time window:* The filter keeps videos from the *last 72 hours** 🧪 Troubleshooting Missing likeCount / classification = "unknown"** → ensure part=statistics and a valid API key credential. Gmail OAuth redirect_mismatch / access_denied** → redirect must be https://<your-n8n-host>/rest/oauth2-credential/callback and test users added if restricted. SMTP auth issues** → set correct server/port/TLS and use an app password when 2FA is enabled. Empty LLM output** → verify OpenAI key/quota and inspect node logs. 🧾 Example Outputs 1) Classification (single video) { "videoId": "abc123XYZ", "title": "How to Ship an n8n Workflow with OpenAI", "likeCount": 1587, "classification": "viral", "needsStatsFetch": false } 2) LinkedIn draft (viral) Did you know how much faster prompt workflows get with structured inputs? • Setup: n8n + YouTube API + OpenAI for auto-briefs • Tip: include part=statistics for reliable like counts Useful for teams tracking trending how-to content. What’s your best “viral” signal besides likes? #n8n #YouTubeAPI #OpenAI #Automation #Growth 3) Plain‑text email preview Subject: Weekly AI Briefing — YouTube Trend Highlights Hi team, Highlights from our tracked channels: • Viral: “How to Ship an n8n Workflow with OpenAI” (1.6k likes) • Normal: “RSS vs API: What’s Best for Monitoring?” Generated via n8n + GPT‑4. ✅ Submission Checklist (meets the guidelines) Title clarity:* Mentions *GPT‑4* and *Gmail** Language:* Entire document in *English** Node naming:** Descriptive, non‑generic labels HTML → Markdown:* No HTML in this description; badges are *Markdown images** Examples:** Included (JSON, LinkedIn draft, email) Security:** No secrets in JSON; uses credentials by name 📸 Suggested Screenshots (optional) Full canvas overview (entire workflow) LLM output (expanded) showing generated summary Send‑node result with messageId/status Optional: aggregated briefing preview 📜 License & Support License: MIT Support/Contact: kaihoelters@yahoo.de

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.

Introduction Automates overseas conference approval requests to CEO. Generates emails with conference details, flight quotes, accommodation, expense breakdown, and admin procedures. Ensures consistency and saves time. How It Works Manual trigger initiates: fetches exchange rates/conference details, parses flight quotes, uses AI to calculate expenses and generate draft, checks budget, formats messages, merges versions, creates PDF, sends to CEO, logs to tracker. Workflow Template Manual Trigger → Configuration → [Exchange Rates + Conference Details + Flight Quotes] → AI Agent → [GPT-4 + Calculate + Extract + Generate Tools] → Total Expenses → Budget Check → [Format Approved + Warning] → Merge → PDF → Send CEO → Log Tracker Workflow Steps Initialization: Manual trigger with conference parameters, sets variables (name, dates, location, funding) Data Collection: Fetches/parses exchange rates, conference details via HTTP, aggregates 3 flight quotations AI Processing: AI Agent orchestrates GPT-4 with Calculate, Extract, Generate tools for expense analysis and email drafting Validation: Calculates total expenses, validates against budget threshold Formatting: Customizes approval/warning messages by status, merges content versions Delivery: Generates PDF breakdown, dispatches via Gmail to CEO, logs to Google Sheets tracker Setup Instructions APIs: Configure currency/conference endpoints with credentials OpenAI: Add GPT-4 API key in AI Agent AI Tools: Set Calculate, Extract, Generate parameters Gmail: Connect account, set CEO recipient Sheets: Link tracker with write permissions Budget: Set threshold (default: $5000) Prerequisites n8n instance, Currency API, Conference API, OpenAI GPT-4 key, Gmail with OAuth, Google Sheets, PDF generator, Travel agent API Use Cases Academic: Staff requests conference with grant, registration, 3 quotes, hotel, visa. AI generates email with PO/card procedures. Sales: Manager seeks client meeting approval with comparisons, per diem. Training: Employee requests certification with fees, accommodation, transport. Customization Modify thresholds by department. Add categories (insurance, baggage). Customize AI prompts for tone/branding. Integrate flight sources. Extend approval chain. Add travel restrictions. Benefits Time Efficient: Reduces prep from 60+ to 5 minutes. AI-Powered: Intelligent analysis and generation. Consistent: Ensures completeness. Accurate: Eliminates errors.

Gmail Lead Reply Analyzer → HubSpot Task + Slack Alert Most sales teams read every email, guess if it’s important, and tell teammates manually. This workflow does it automatically: check intent and sentiment with AI, create follow-up tasks, send Slack alerts, and save everything to Google Sheets. Benefits AI checks sentiment, intent, urgency, and priority Creates HubSpot tasks only if follow-up is needed Sends Slack message with lead summary Logs all results to Google Sheets for tracking Runs 24/7 with no manual sorting How It Works Gmail trigger watches a label for new replies Workflow extracts sender, subject, and message AI analyzes message and returns: sentiment, intent, urgency, next step Code step cleans result, adds date, and checks if follow-up is needed If follow-up = yes → create HubSpot task, send Slack alert, log to Sheets If follow-up = no → just log to Sheets Who Is This For Sales teams getting many leads by email Founders who handle leads themselves Agencies needing clear and fast lead triage Setup Connect Gmail (choose or create label) Add OpenAI API key (model: GPT-4o mini) Connect HubSpot (App Token for tasks) Connect Slack (channel for alerts) Connect Google Sheets (Spreadsheet + Tab) Optional: change how urgency/priority is scored in the code ROI & Monetization Save 3–6 hours per week on email sorting Answer faster and close more deals Sell as $1k–$3k/month “inbox automation” service Strategy Insights In the full walkthrough, I show how to: Make sure AI always returns valid JSON Adjust what counts as a follow-up lead Format Slack messages for quick reading Use Google Sheets as a simple dashboard Check Out My Channel For more AI automation systems that get real results, check out my YouTube channel where I share exactly how I build automation workflows, sell high-value services, and scale to $20k+ monthly revenue.

How It Works Telegram Trigger** receives incoming messages (text, voice, photo, document). Switch** routes by message type to appropriate processors: Text → forwarded as-is. Voice → downloaded and sent to Transcribe a recording. Photo → downloaded, converted to base64, then sent to Analyze image. Document → routed to document handler. Merge* collects the processed input and passes a unified prompt to *Manager Agent**. Manager Agent (LM: Google Gemini)** orchestrates specialized agents/tools: memory_base (Airtable) → saving & retrieving personal/company memory todo_and_task_manager (Todoist / Google Sheets) → tasks email_agent (Gmail) → composing/sending emails calendar_agent (Google Calendar) → scheduling research_agent (SerpAPI / Wikipedia / Wolfram) → web research project_management (Google Sheets) → project updates Manager Agent** updates memory windows and sends the final reply back to Telegram. Setup Steps Create and configure Telegram bot; set bot token/webhook in Telegram Trigger and Telegram nodes. Update chatId placeholders. Add Google Gemini (PaLM) credentials in the Gemini model nodes. Configure Airtable knowledge-base: set base ID & table IDs used by memory_base nodes. Connect Google APIs: Sheets, Calendar, Gmail credentials and set document/sheet IDs. Configure Todoist, SerpAPI, WolframAlpha credentials and any other tool API keys. Verify Window Buffer Memory sessionKey values (match user sessions). Check schedule triggers (cron expressions) and adjust times/timezone. Run quick tests: send text, voice, image, and confirm replies and memory writes. Estimated Setup Time 30–60 minutes** → if credentials & IDs are ready. 2–4 hours** → full setup (API keys, spreadsheets, Airtable, detailed permissions). 4–8 hours** → complex deployment (team permissions, multiple calendars, advanced tool tuning, production testing).

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.

How it works • Twilio webhook detects missed/unanswered calls automatically • Analyzes call context (time of day, business hours, weekend/weekday) • Checks CRM for existing customer data and purchase history (optional) • AI Chain (GPT-4o) generates personalized recovery messages for SMS and Email • Sends instant apology with booking link via SMS and/or Email • Logs all interactions to Airtable for tracking • Slack alerts sales team with customer priority and context • Waits 24 hours and checks if customer booked • Sends automatic follow-up SMS if no booking detected • Structured output parser ensures reliable JSON formatting Set up steps • Time to set up: 15-20 minutes • Add Twilio credential and configure phone number in both SMS nodes • Get Slack channel ID for sales team alerts • Create Airtable base with 10 columns (Caller_Number, Customer_Name, Call_Time, Priority, SMS_Sent, Email_Sent, Booking_Link, Status, Urgency_Score, Follow_Up_Date) • Replace booking URL with your Cal.com or Calendly link • Configure business email for SMTP sending • Update business phone and name in follow-up SMS • Add credentials: Twilio API, OpenAI (GPT-4o), Slack OAuth2, Airtable Token, SMTP Email • Replace placeholder IDs in Slack and Airtable nodes • Optional: Configure CRM API for existing customer lookup (or disable those nodes) What you'll need • Twilio - Phone number with SMS capability • OpenAI API - GPT-4o access for AI message generation • Slack - Standard workspace for sales alerts • Airtable - Free plan works for call tracking • Email SMTP - Gmail, SendGrid, or any SMTP provider • Cal.com or Calendly - Booking link for instant scheduling • CRM API (optional) - HubSpot, Salesforce, or custom CRM Who this is for Service businesses, agencies, and sales teams that lose revenue from missed calls. Perfect for businesses with high call volume that need instant personalized follow-up to recover lost opportunities.

How it works Watches a Google Drive folder for new (scanned) invoices. Each new file automatically triggers the workflow. Downloads and processes each invoice through OCR Space to extract the text. Extracts the company name (e.g. from the “billed to” field) and uses an AI agent to cross-reference it against a database in Google Sheets. If a match is found, retrieves the correct recipient email and sends the invoice as an attachment. If no match or an error occurs, the workflow alerts an operator by email for manual review. Setting up the workflow Connect Google Drive • In n8n, connect your Google Drive account. • Create or select a folder where you will upload scanned invoices. Connect Gmail (or another email service) • Add your Gmail account as a credential in n8n. • This will be used to send the processed invoice to the correct recipient. Set up OCR.Space • Create a free OCR.Space account: https://ocr.space • In n8n, create a Generic Credential (Header Auth). • Use apikey as the name and your OCR API key as the value. Connect the AI Agent • Add your OpenAI API key as a credential in n8n. • The AI Agent will extract the company name from the invoice text and match it against your database. • If a match is found, it retrieves the correct email. Prepare the Google Sheet database • Make a copy of the database sheet: Google Sheet Template • Fill it with company names and recipient emails. • Connect your Google account to n8n and link this sheet to the workflow. Run the workflow • When a new invoice is uploaded to your Google Drive folder, the workflow will: • Extract the text with OCR.Space • Use the AI Agent to identify the company name • Cross-reference it with your Google Sheet database • Send the invoice automatically to the correct recipient via Gmail • If no match is found, an error email is sent to you for manual review

Introduction Automates travel planning by aggregating flights, hotels, activities, and weather via APIs, then uses AI to generate professional itineraries delivered through Gmail and Slack. How It Works Webhook receives requests, searches APIs (Skyscanner, Booking.com, Kiwi, Viator, weather), merges data, AI builds itineraries, scores options, generates HTML emails, delivers via Gmail/Slack. Workflow Template Webhook → Extract → Parallel Searches (Flights/Hotels/Activities/Weather) → Merge → Build Itinerary → AI Processing → Score → Generate HTML → Gmail → Slack → Response Workflow Steps Trigger & Extract: Receives destination, dates, preferences, extracts parameters. Data Gathering: Parallel APIs fetch flights, hotels, activities, weather, merges responses. AI Processing: Analyzes data, creates itinerary, ranks recommendations. Delivery: Generates HTML email, sends via Gmail/Slack, confirms completion. Setup Instructions API Configuration: Add keys for Skyscanner, Booking.com, Kiwi, Viator, OpenWeatherMap, OpenRouter. Communication: Connect Gmail OAuth2, Slack webhook. Customization: Adjust endpoints, AI prompts, HTML template, scoring criteria. Prerequisites API keys: Skyscanner, Booking.com, Kiwi, Viator, OpenWeatherMap, OpenRouter Gmail account Slack workspace n8n instance Use Cases Corporate travel planning Vacation itinerary generation Group trip coordination Customization Add sources (Airbnb, TripAdvisor) Filter by budget preferences Add PDF generation Customize Slack format Benefits Saves 3-5 hours per trip Real-time pricing aggregation AI-powered personalization Automated multi-channel delivery

Introduction Automates Singapore COE price tracking with AI forecasts and buy/wait recommendations. Weekly scraping collects LTA data, enriches with economic indicators, predicts 6-month trends, and alerts users via Telegram/email—helping car buyers and fleet managers make data-driven purchase decisions while avoiding manual tracking. How it Works Weekly trigger scrapes LTA COE → validates → stores in Google Sheets → calculates indicators → AI forecasts trends → multi-scenario analysis → generates buy/wait signals → sends actionable alerts. Setup Steps Add OpenAI/NVIDIA API credentials in n8n Authenticate Google Sheets and create spreadsheet Configure Telegram bot or Gmail SMTP Set weekly trigger (Thursday 9AM SGT post-bidding) Adjust alert thresholds in conditional nodes Workflow Schedule Trigger → Scrape COE → Validate → Store Sheets → Fetch Historical → Calculate Indicators → AI Prediction → Merge Economics → Multi-Scenario Analysis → Compare Conditions → Generate Dashboard → Send Alerts Workflow Steps Scraping: Fetch LTA COE results with retry logic Validation: Check completeness, flag anomalies Storage: Append timestamped records to Sheets Enrichment: Calculate moving averages, volatility, seasonality AI Analysis: Forecast next 6 months with confidence intervals Decision Engine: Output buy/wait/monitor recommendation Reporting: Create dashboard and send alerts via Telegram/email Prerequisites OpenAI/NVIDIA API key, Google Sheets access, Telegram bot token or Gmail, basic COE category understanding Use Cases First-time buyers timing purchases, fleet operators coordinating bulk acquisitions Customization Add SMS alerts via Twilio, integrate loan calculators for total cost analysis Benefits Saves 5+ hours monthly, captures 10–18% price dips, provides predictive insights (potential $10K–$25K savings)