Workflow Templates

How it works This template is an interactive, step-by-step tutorial designed to teach you the most important skill in n8n: using expressions to access and manipulate data. If you know what JSON is but aren't sure how to pull a specific piece of information from one node and use it in another, this workflow is for you. It starts with a single "Source Data" node that acts as our filing cabinet, and then walks you through a series of lessons, each demonstrating a new technique for retrieving and transforming that data. You will learn how to: Access a simple value from a previous node. Use n8n's built-in selectors like .last() and .first(). Get a specific item from a list (Array). Drill down into nested data (Objects). Combine these techniques to access data in an array of objects. Go beyond simple retrieval by using JavaScript functions to do math or change text. Inspect data with utility functions like Object.keys() and JSON.stringify(). Summarize data from multiple items using .all() and arrow functions. Set up steps Setup time: 0 minutes! This workflow is a self-contained tutorial and requires no setup or external credentials. Click "Execute Workflow" to run the entire tutorial. Follow the flow from the "Source Data" node to the "Final Exam" node. For each lesson, click on the node to see how its expressions are configured in the parameters panel. Read the detailed sticky note next to each lesson—it breaks down exactly how the expression works and why. By the end, you'll have the foundational knowledge to connect data and build powerful, dynamic workflows in n8n.

📝 Description 🤖 What this workflow does This workflow turns Reddit pain points into emotionally-driven comic-style ads using AI. It takes in a product description, scrapes Reddit for real user pain points, filters relevant posts using AI, generates ad angles, rewrites them into 4-panel comic prompts, and finally uses Dumpling AI to generate comic-style images. All final creatives are uploaded to Google Drive. 🧠 What problem is this solving? Crafting ad content that truly speaks to customer struggles is time-consuming. This workflow automates that entire process — from pain point discovery to visual creative output — using AI and Reddit as a source of truth for customer language. 👤 Who is this for? Copywriters and performance marketers Startup founders and indie hackers Creatives building empathy-driven ad concepts Automation experts looking to generate scroll-stopping content ⚙️ Setup Instructions Here’s how to set everything up, step by step: 🔹 1. Trigger: Form Input Node: 📝 Form - Submit Product Info This form asks the user to enter: Brand Name Website Product Description ✅ Make sure this form is active and testable. 🔹 2. Generate Reddit Keyword Node: 🧠 GPT-4o - Generate Reddit Keyword Uses the product description to generate a search keyword based on what your audience might be discussing on Reddit. 🔹 3. Search Reddit Node: 🔍 Reddit - Search Posts Uses the keyword to search Reddit for relevant threads. Make sure your Reddit integration is properly configured. 🔹 4. Filter Valid Posts Node: 🔎 IF - Check Upvotes & Text Length Filters out low-effort or unpopular posts. Only keeps posts with: Minimum 2 upvotes Content at least 100 characters long ✅ You can adjust these thresholds in the node settings. 🔹 5. Clean Reddit Output Node: 🧼 Code - Structure Reddit Posts This formats the list of posts into clean JSON for the AI agents to process. 🔹 6. Check Relevance with AI Agent Node: 🤔 Langchain Agent - Post Relevance Classifier This node uses a LangChain agent (tool: think2) to determine if each post is relevant to your product. Only relevant ones are passed forward. 🔹 7. Aggregate Relevant Posts Node: 📦 Code - Merge Relevant Posts Collects all relevant posts into a clean format for the next GPT-4 call. 🔹 8. Generate Ad Angles Node: ✍️ GPT-4o - Generate Emotional Ad Angles Writes 10 pain-point-based marketing angles using real customer language. 🔹 9. Rank the Best Angles Node: 📊 GPT-4o - Rank Top 10 Angles Scores the generated angles and ranks them from most to least powerful. Only the top 3 are passed forward. 🔹 10. Turn Angles into Comic Prompts Node: 🎭 GPT-4o - Write Comic Scene Prompts Rewrites each of the top ad angles into a 4-panel comic strip structure (pain → tension → product → resolution). 🔹 11. Generate Comic Images Node: 🎨 Dumpling AI - Generate Comic Panels Sends each prompt to Dumpling AI to create visual comic scenes. 🔹 12. Wait for Image Generation Node: ⏳ Wait - Dumpling AI Response Time Adds a delay to give Dumpling AI time to finish generating all images. 🔹 13. Get Final Image URLs Node: 🔗 Code - Extract Image URLs from Dumpling Response Extracts all image links for preview/download. 🔹 14. Upload to Google Drive Node: ☁️ Google Drive - Upload Comics Uploads the comic images to your chosen Google Drive folder. ✅ Update this node with your destination folder ID. 🔹 15. Log Final Output Optional You can extend the flow to log the image links, ad angles, and Reddit sources to Google Sheets, Airtable, or Notion depending on your use case. 🛠️ How to Customize ✏️ Adjust tone: Update GPT-4 system prompts to sound more humorous, emotional, or brand-specific. 🧵 Use different styles: Swap Dumpling AI image settings for ink sketch, manga, or cartoon renderings. 🔄 Change input source: Replace Reddit with X (Twitter), Quora, or YouTube comments. 📦 Store results differently: Swap Google Drive for Notion, Dropbox, or Airtable. This workflow turns real audience struggles into thumb-stopping comic content — automatically.

Community Node Disclaimer: This workflow uses KlickTipp community nodes. How It Works AI Agent and KlickTipp Tools Integration via Telegram: This component connects a large language model (LLM), such as Claude or OpenAI, to the KlickTipp contact management platform through Telegram messaging. The AI Agent interprets natural language queries received from Telegram and dynamically maps them to KlickTipp API operations, enabling intuitive and automated contact handling through a familiar messaging interface. Key Features Telegram & LLM Interaction Setup: Captures messages received via Telegram bot as an alternative to the chat message node. Maintains conversation state using a memory buffer tied to Telegram chat IDs. Interprets user input using an LLM (Claude or OpenAI). Routes interpreted commands to specific KlickTipp tools based on detected intent. Sends responses back to Telegram users with operation results. KlickTipp Integration: Complete set of KlickTipp API endpoints included: Contact Management:** Add, update, get, list, delete, and unsubscribe contacts. Contact Tagging:** Tag, untag, list tagged contacts. Tag Operations:** Create, get, update, delete, list tags. Opt-In Processes:** List and retrieve opt-in process details. Data Fields:** List and get custom data fields. Redirects:** Retrieve redirect URLs. Use Cases Supported: Query contact information via email or name through Telegram messages. Identify and segment contacts by city, region, or behavior via Telegram commands. Create or update contacts from data provided in Telegram messages. Dynamically apply or remove tags to initiate campaigns through Telegram bot interactions. Automate targeted outreach based on contact attributes using Telegram as the control interface. Setup Instructions Install and Configure Nodes: Set up a Telegram bot using BotFather and obtain the bot token. Configure the Telegram Trigger node in n8n with your bot token. Configure the LLM model (e.g., OpenAI or Claude) and memory node if used. Connect all required KlickTipp nodes and authenticate using valid API credentials. Activate the workflow. Define Tagging and Field Mapping: Identify which fields and tags are relevant to your use cases. Ensure necessary tags and custom fields are already created in KlickTipp. Workflow Logic: Trigger via Telegram: A message is received by the Telegram bot and passed to the AI Agent. Query Handling via LLM Agent: AI interprets the natural language input and determines the action. Contact Search & Segmentation: Searches contacts using identifiers (email, address) or criteria. Data Operations: Retrieves, updates, or manages contact and tag data based on interpreted command. Campaign Preparation: Applies tags or sends campaign triggers depending on query results. Response via Telegram: Sends formatted results back to the Telegram user. Benefits: Mobile-First Interface:** Users can manage KlickTipp contacts directly from Telegram on any device. AI-Powered Automation:** Reduces manual contact search and tagging efforts through intelligent processing. Scalable Integration:** Built-in support for full range of KlickTipp operations allows diverse use-case handling. Data Consistency:** Ensures structured data flows between Telegram, AI, and KlickTipp, minimizing errors. Testing and Deployment: Use defined Telegram messages such as: “Tell me something about the contact with email address X” “Tag all contacts from region Y” “Send campaign Z to customers in area A” Validate expected actions in KlickTipp after message execution and confirm responses in Telegram. Notes: Customization:** Adjust tag logic, AI prompts, and contact field mappings based on project needs. Extensibility:** The template can be expanded with further logic for Google Sheets input or campaign feedback loops Resources: Use KlickTipp Community Node in n8n Automate Workflows: KlickTipp Integration in n8n

Automated Financial Reporting Using Google Vision OCR, Telegram & Google Sheets This workflow automates the process of recording financial transactions from photos of receipts or shopping receipts. Users simply send an image of the receipt via Telegram. The image is processed using the Google Vision API to detect text, then extracted and structured by LLM via OpenRouter. The final result is saved to Google Sheets and also displayed to the user via a Telegram bot. 🧾 Google Sheets Template Create a Google Sheet using this template: Financial Reporting 🛠️ Key Features The workflow starts when a user sends a photo of a receipt to the Telegram bot. The image is converted to text using the Google Vision API's OCR. Data processing with LLM (OpenRouter) helps identify and structure transaction elements such as: date, vendor name & address, receipt/invoice number, item list (product name, quantity, unit price, total), and transaction category. Cleaned and structured data is automatically recorded to Google Sheets per item. The system also sends a summary of the recording results in an easy to read text format. Users can also send text messages to the bot to query stored transaction data, which will be answered by a Google Sheets-based AI Agent. 🔧 Requirements Active Telegram Bot + API Token Google Vision API Key OpenRouter Account + API Key Google Sheets connected to n8n 🧩 Setup Instructions Replace all API keys and tokens with your own in the relevant nodes. Google Vision API Key: Set in 'Set Vision API' node. Telegram Bot Token: Set in 'Set Telegram Token' node and all Telegram nodes. OpenRouter API Key: Set in all OpenRouter nodes. Google Sheets: Connect your own Google Sheets credential. Use the provided Google Sheets template or your own. Activate the workflow after configuration. (Optional) Review sticky notes for step-by-step explanations.

How it works This template is a hands-on, practical exam designed to test your understanding of the fundamental JSON data types. It's the perfect way to solidify your knowledge after learning the basics. Think of it as the "driver's test" that comes after the "theory lesson". You'll be given a series of tasks, and the workflow will automatically check your answers, providing instant feedback. The test is broken down into six sequential challenges, each focusing on a core data type: String: Writing text values correctly. Number: Using integers and decimals. Boolean: Working with true and false. Null: Representing a non-existant value. Array: Creating ordered lists of data. Object: Building nested key-value structures. For each challenge, you'll modify a Set node with the correct JSON syntax. When you execute the workflow, a corresponding IF node will validate your input. A green path means you passed and can move to the next challenge. A red path means you need to try again! Set up steps Setup time: < 1 minute This workflow is a self-contained test and requires no setup or credentials. Read the instructions on the main sticky note to understand the goal. Start with the first challenge, "Test - String". Activate and modify the node according to the instructions on the purple sticky note next to it. Click "Execute Workflow". If the execution path is green, you've passed! You can move on to the next "Test" node in the sequence to continue. If the path is red, read the hint in the error message and try again. Repeat the process until you reach the final success message. Good luck!

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This comprehensive RAG workflow enables your AI agents to answer user questions with contextual knowledge pulled from your own documents — using metadata-rich embeddings stored in Supabase. 🔧 Key Features: RAG Agents powered by GPT-4.5 or GPT-3.5 via OpenRouter or OpenAI. Supabase Vector Store to store and retrieve document embeddings. Cohere Reranker to improve response relevance and quality. Metadata Agent to enrich vectorized data before ingestion. PDF Extraction Flow to automatically parse and upload documents with metadata. ✅ Setup Steps: Connect your Supabase Vector Store. Use OpenAI Embeddings (e.g. text-embedding-3-small). Add API keys for OpenAI and/or OpenRouter. Connect a reranker like Cohere. Process documents with metadata before embedding. Start chatting — your AI agent now returns context-rich answers from your own knowledge base! Perfect for building AI assistants that can reason, search and answer based on internal company data, academic papers, support docs, or personal notes.

👔 Who is this for? Entrepreneurs and startup founders preparing for investors Business consultants drafting complete client plans Strategy teams building long-term business models Accelerators, incubators, or pitch trainers ❓ What problem does this workflow solve? Writing a full business plan takes days of work, multiple tools, and often gets stuck in messy docs or slides. This template automates every major section, generating a clean, detailed, and professional business plan with AI in just minutes. ⚙️ What this workflow does Starts with a chat message asking for your business idea or startup concept Passes the idea through 83 intelligent agents, each handling a full business plan chapter: Executive Summary Problem & Solution Product Description Market Research Competitor Analysis Business Model Marketing Strategy (includes guerrilla ideas) Operational Plan Financial Plan Team & Advisors Roadmap Conclusion & Next Steps Each section uses tailored prompts and business logic Combines all outputs into a structured, professional Markdown file Final result: a ready-to-export business plan in seconds 🛠️ Setup Import this template into your n8n instance Replace the “LLM Chat Model” node with your preferred model (Ollama, GPT-4, etc.) Start from the chat input node — describe your startup or idea Wait for all agents to finish Download the final Business plan file 🤖 LLM Flexibility (Choose Your Model) Supports: OpenAI (GPT-4 / GPT-3.5) Ollama (LLaMA 3.1, Mistral, DeepSeek, etc.) Any compatible N8N chat model To change the model, just replace the “Language Model” node — no other updates required 📌 Notes All nodes are clearly named by function (e.g., “Market Research Generator”) Sticky notes included for clarity Generates high-quality plans suitable for VCs or accelerators Modular: you can turn off or reorder any chapter 📩 Need help? Email: sinamirshafiee@gmail.com Happy to support setup, LLM switching, or custom section development.

This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions. This template is intended to help introduce n8n users interested in building with WhatsApp. How it works This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot. A product brochure is imported via HTTP request node and its text contents extracted. The text contents are then uploaded to the in-memory vector store to build a knowledgebase for the chatbot. A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out. The customer's message is sent to the AI Agent which queries the product catalogue using the vector store tool. The Agent's response is sent back to the user via the WhatsApp node. How to use Once you've setup and configured your WhatsApp account and credentials First, populate the vector store by clicking the "Test Workflow" button. Next, activate the workflow to enable the WhatsApp chatbot. Message your designated WhatsApp number and you should receive a message from the AI sales agent. Tweak datasource and behaviour as required. Requirements WhatsApp Business Account OpenAI for LLM Customising this workflow Upgrade the vector store to Qdrant for persistance and production use-cases. Handle different WhatsApp message types for a more rich and engaging experience for customers.

🎧 Daily RSS Digest & Podcast Generation This workflow automates the creation of a daily sports podcast from your favorite news sources. It fetches articles, uses AI to write a digest and a two-person dialogue, and produces a single, merged audio file with KOKORO TTS ready for listening. ✨ How it works: 📰 Fetch & Filter Daily News: The workflow triggers daily, fetches articles from your chosen RSS feeds, and filters them to keep only the most recent content. ✍️ Generate AI Digest & Script: Using Google Gemini, it first creates a written summary of the day's news. A second AI agent then transforms this news into an engaging, conversational podcast script between two distinct AI speakers. 🗣️ Generate Voices in Chunks: The script is split into individual lines of dialogue. The workflow then loops through each line, calling a Text-to-Speech (TTS) API to generate a separate audio file (an MP3 chunk) for each part of the conversation. 🎛️ Merge Audio with FFmpeg: After all the audio chunks are created and saved locally, a command-line script generates a list of all the files and uses FFmpeg to losslessly merge them into a single, seamless MP3 file. All temporary files are then deleted. 📤 Send the Final Podcast: The final, merged MP3 is read from the server and delivered directly to your Telegram chat with a dynamic, dated filename. You can modify: 📰 The RSS Feeds to any news source you want. 🤖 The AI Prompts to change the tone, language, or style of the digest and podcast. 🎙️ The TTS Voices used for the two speakers. 📫 The Final Delivery Method (e.g., send to Discord, save to Google Drive, etc.). Perfect for creating a personalized, hands-free news briefing to listen to on your commute. Inspired by: https://n8n.io/workflows/6523-convert-newsletters-into-ai-podcasts-with-gpt-4o-mini-and-elevenlabs/

Automated Cryptocurrency Analysis & Reporting with Google Gemini and CoinGecko This powerful template is an n8n workflow that automates cryptocurrency market data analysis and delivers reports directly to your inbox. It fetches real-time data from CoinGecko API, generates AI-powered analysis, and sends the report via email. Features Scheduled Execution**: Runs automatically at a set time daily (default: 10:00 AM). Customizable Analysis**: Personalize analysis content/language via "AI Prompt" nodes. Easy Scalability**: Duplicate node groups to add more cryptocurrencies. Flexible AI Integration**: Defaults to Google Gemini, but supports ChatGPT/Ollama. Setup Instructions n8n Installation: Install n8n (self-hosted or Cloud version). Email Account Setup: Add email service credentials in n8n (e.g., Microsoft Outlook OAuth2). AI Model Credentials (Google Gemini): Obtain API key from Google AI Studio and add to n8n "Credentials". Import Template: Copy the JSON code into n8n as a new workflow. Customization Change Cryptocurrencies**: Update ids= parameter in HTTP Request nodes (e.g., ids=bitcoin). Edit AI Prompt**: Modify text in "AI Prompt" nodes. Use Different AI Model**: Replace Google Gemini with supported alternatives. Update Email Address**: Change recipient in "Send Mail" nodes. `

Disclaimer: Community nodes are used, and template can only be used on self-hosted n8n instances. This n8n template from Intuz provides a complete solution to automate your entire B2B lead generation pipeline, from discovering recently funded companies to drafting hyper-personalized outreach emails with AI. Who's this workflow for? Sales Development Representatives (SDRs) Business Development Teams Growth Hackers Startup Founders Marketing Agencies How it works 1. Scrape Funded Companies: The workflow begins by using Apify to scrape a target list of recently funded companies directly from a Crunchbase search. 2. Enrich with Apollo.io: It takes each company and uses the Apollo.io API to find key decision-makers (like VPs, Directors) and enrich their contact information, including finding their email addresses. 3. Populate Google Sheets: All the gathered lead data—company name, contact name, title, email, LinkedIn URL, etc.—is neatly organized and added to a Google Sheet. 4. AI-Personalized Email Crafting: The workflow sends the lead's information to OpenAI (GPT-4) with a highly specialized prompt, instructing it to write a concise, impactful, and hyper-personalized "first touch" cold email. 5. Update Lead List with Email Content: Finally, the unique, AI-generated email is saved back into the Google Sheet alongside the corresponding lead's information, making it ready for you to send. Pre-conditions and Requirements Before you can successfully execute this workflow, you must have the following accounts, credentials, and assets in place. 1. n8n Instance: You need an active n8n instance (self-hosted). 2. Apify Account & Crunchbase Access: Apify Account: A registered account on Apify. Crunchbase Account: An active, logged-in Crunchbase account (a paid subscription is recommended for accessing detailed search filters). 3. Apollo.io API: You need an Apollo.io plan that includes API access. You can generate the API from settings. 4. Google Sheet: Create a new Google Sheet to store your leads. The workflow is configured for two tabs: one for raw data ("HealthCare" in the template) and one for email generation ("Company sheet"). 5. OpenAI Account: An account with OpenAI with API access and billing set up. Setup Instructions 1. Apify Connection: Connect your Apify account in the Run an Actor node. You'll need an apify scrapper, here's the link In the Custom Body field, update the search.url with your target Crunchbase discovery URL and provide a valid cookie for authentication. 2. Apollo.io Connection: Connect your Apollo.io account using HTTP Header Authentication in the three Apollo nodes. You will need to provide your API key. 3. Google Sheets Connection: Connect your Google Sheets account. Create a spreadsheet and update the Document ID and Sheet Name in the three Google Sheets nodes to match yours. Ensure your sheet columns are set up to receive the data. 4. OpenAI Connection: Connect your OpenAI account in the Message a model node. The prompt is pre-engineered for high-quality output, but you can tailor it to better fit your specific value proposition. 5. Activate Workflow: Click "Execute workflow" to run the automation manually and watch your AI-powered lead list build itself. Customization Guide This workflow is a powerful template. To adapt it to your specific business needs, you should review and modify the following nodes. 1. Changing Your Target Companies (The Source) Node: Run an Actor What to change: The search.url parameter inside the customBody. How to do it: Go to Crunchbase and perform a search for your ideal companies (e.g., filter by different funding rounds, industry, location, keywords, etc.). Copy the URL from your browser's address bar after the search results have loaded. Paste this new URL as the value for "search.url" in the node. You can also adjust "count": 10 to pull more or fewer companies per run. Be mindful of Apify and Apollo credit usage. 2. Defining Your Ideal Contact Persona Node: Apollo - Get User What to change: The person_seniorities and person_titles arrays in the jsonBody. How to do it: 1. Seniority: Modify the person_seniorities list to match who you sell to. Examples: ["c_level", "founder"] or ["manager", "contributor"]. 2. Job Titles: This is crucial. Replace the existing list of titles ("engineering", "technology", etc.) with keywords relevant to your target buyer. For example, if you sell to marketing teams, you might use: ["marketing", "demand generation", "growth", "content", "brand"]. 3. Configuring Your Google Sheet Destination Nodes: Append or update row in sheet and Update row in sheet What to change: The documentId and sheetName. How to do it: Open your Google Sheet. The documentId is the long string of characters in the URL between /d/ and /edit. Copy and paste it into the "Document ID" field in both nodes. The sheetName (or Sheet ID/gid) needs to be set for your specific tabs. Make sure the sheet names/IDs in the nodes match the tabs in your document. Column Mapping: If you change the column names in your Google Sheet, you must update the column mapping inside these nodes to ensure the data is written to the correct place. 4. Tailoring the AI Email Generation Node: Message a model (OpenAI) What to change: The prompt, the model, and the input variables. How to do it: The Prompt: This is the heart of your outreach. Read the entire prompt carefully and edit it to reflect your company's value proposition, tone of voice, and specific call-to-action. Value Proposition: Change the line "We help them cut that specific infrastructure spend..." to match what your product does. Use a powerful, single data point if you have one. Call-to-Action (CTA): Modify the final question ("Curious if infra efficiency is on your roadmap...") to something that fits your sales process. Tone: Adjust the initial instructions (e.g., "Your tone is that of a peer...") if you want a different style. The Model: The workflow uses gpt-4.1. You can switch to a different model like gpt-4o (potentially better/faster) or gpt-3.5-turbo (much cheaper, but lower quality) depending on your budget and needs. Input Variables: The prompt uses {{ $json['Company Name'] }}, {{ $json['Person Designation'] }}, and {{ $json.Industry }}. If you want to add more personalization (e.g., based on a company's funding amount), you would first need to ensure that data is passed to this node, then add the new variable (e.g., {{ $json['Funding Amount'] }}) into the prompt. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Workflow Automation Click here- Get Started

Instantly fetch real-time Bitget spot market data directly in Telegram! This workflow integrates the Bitget REST v2 API with Telegram (plus optional AI-powered formatting) to deliver the latest crypto price, order book, candles, and recent trades. Perfect for crypto traders, analysts, and investors who need reliable market data at their fingertips—no API key required.  Sign-up for Bitget for 6,200 USDT in rewards to trade: Collect Now How It Works A Telegram bot listens for user requests (e.g., BTCUSDT). The workflow connects to Bitget public endpoints to fetch: Ticker (latest price & 24h stats) Order book depth (top bids/asks) Recent trades (price, side, volume, timestamp) Candlestick data (1m, 15m, 1h, 4h, 1d) Historical candles (optional, for backfill before endTime) A Calculator node derives useful metrics like mid-price and spread. A Think node reshapes raw JSON into Telegram-ready text. A splitter ensures reports over 4000 characters are chunked safely. The final market insights are delivered instantly back to Telegram. What You Can Do with This Agent ✅ Track live prices & 24h stats for any Bitget spot pair. ✅ Monitor order book liquidity and spreads in real-time. ✅ Analyze candlesticks across multiple timeframes. ✅ Review recent trades to see execution flow. ✅ Fetch historical candles for extended market context. ✅ Receive clean, structured reports with optional AI-enhanced formatting. Set Up Steps Create a Telegram Bot Use @BotFather to generate a bot token. Configure in n8n Import Bitget AI Agent v1.02.json into your n8n instance. Add your Telegram credentials (bot token + your Telegram ID in the User Authentication node). Add an OpenAI key if you want AI-powered formatting. (Optional) Add an *Bitget api key** . Deploy and Test Send BTCUSDT to your bot. Get live Bitget spot data instantly in Telegram! 🚀 Unlock powerful, real-time Bitget insights in Telegram—zero setup, zero API keys required! 📺 Setup Video Tutorial Watch the full setup guide on YouTube: 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn