Workflow Templates

How it works • Webhook receives lead form submissions from your website • AI Agent (GPT-4o) analyzes lead quality using intelligent scoring framework • Clearbit enriches company data automatically (employee count, industry, revenue) • Qualification score (0-100) determines routing: high-quality leads → HubSpot CRM + Slack alert, low-quality leads → Airtable for manual review • Structured output parser ensures reliable JSON formatting every time Set up steps • Time to set up: 15-20 minutes • Import the Clearbit sub-workflow first (separate workflow file included) • Create 7 custom properties in HubSpot (qualification_score, buying_intent, urgency_level, budget_indicator, ai_summary, pain_points, recommended_action) • Create Airtable base with 14 columns for low-quality lead tracking • Get Slack channel IDs for sales alerts and review requests • Add credentials: OpenAI (GPT-4o), Clearbit API, HubSpot OAuth2, Slack OAuth2, Airtable Token • Replace placeholder IDs in Slack and Airtable nodes • Configure the Clearbit Enrichment Tool node with your sub-workflow ID What you'll need • OpenAI API - OpenAI model access for AI qualification • Clearbit API - Free tier available for company enrichment • HubSpot - Free CRM account works • Slack - Standard workspace • Airtable - Free plan works • Website form - To send webhook data Who this is for Sales teams and agencies that want to automatically qualify inbound leads before they hit the CRM. Perfect for B2B companies with high lead volume that need intelligent routing.

Revolut Extracts Analyzer This n8n template processes Revolut statements, normalizes transactions, and uses AI to categorize expenses automatically. Use cases include detecting subscriptions, separating internal transfers, and building dashboards to track spending. How it works Get Categories from Supabase** Download & Transform** Loop Over Items** LLM Categorizer** Insert into Supabase** How to use Start with the manual trigger node or replace it with a schedule/webhook. Connect Google Drive to provide Revolut CSV files. Ensure Supabase has tables for transactions and categories. Extend with notifications, reports, or BI tools. Requirements Google Drive for CSV files Supabase tables for categories & transactions LLM provider (OpenAI/Gemini)

👥 Who's it for This workflow is perfect for businesses or individuals who want to automate WhatsApp conversations 💬 with an intelligent AI chatbot that can handle text, voice notes 🎵, and images 🖼️. No advanced coding required! 🤖 What it does It automatically receives WhatsApp messages through WasenderAPI, intelligently buffers consecutive messages to avoid fragmented responses, processes multimedia content (transcribing audio and analyzing images with AI), and responds naturally using GPT-4o mini with conversation memory. All while protecting your WhatsApp account from being banned. ⚙️ How it works 📱 Webhook Trigger – Receives new messages from WasenderAPI 🗃️ Redis Buffer System – Groups consecutive messages intelligently (7-second window) 🔀 Content Classifier – Routes messages by type (text, audio, or image) 🎵 Audio Processing – Decrypts and transcribes voice notes using OpenAI Whisper 🖼️ Image Analysis – Decrypts and analyzes images with GPT-4O Vision 🧠 AI Agent (GPT-4o mini) – Generates intelligent responses with 10-message memory ⏱️ Anti-Ban Wait – 6-second delay to simulate human typing 📤 Message Sender – Delivers response back to WhatsApp user 📋 Requirements WasenderAPI account with connected WhatsApp number : https://wasenderapi.com/ Redis database (free tier works fine) OpenAI API key with access to GPT-4o mini and Whisper n8n's AI Agent, LangChain, and Redis nodes 🛠️ How to set up Create your WasenderAPI account and connect a WhatsApp number Set up a free Redis database and get connection credentials Configure OpenAI API key in n8n credentials Replace the WasenderAPI Bearer token in "Get the audio", "Get the photo", and "Send Message to User" nodes Change the Manual Trigger to a Webhook and configure it in WasenderAPI Customize the AI Agent prompt to match your business needs Adjust wait times if needed (default: 6 seconds for responses, 7 seconds for buffer) Save and activate the workflow ✅ 🎨 How to customize Modify the AI Agent prompt to change bot personality and instructions Adjust buffer wait time (7 seconds) for faster/slower message grouping Change response delay (6 seconds) based on your use case , its recomendable 30 seconds. Add more content types (documents, videos) by extending the Switch Type node Configure conversation memory window (default: 10 messages)

What Problem Does It Solve? Customers often ask product questions or prices in comments. Businesses waste time replying manually, leading to delays. Some comments only need a short thank-you reply, while others need a detailed private response. This workflow solves these by: Replying with a friendly public comment. Sending a private message with details when needed. Handling compliments, complaints, and unclear comments in a consistent way. How to Configure It Facebook Setup Connect your Facebook Page credentials in n8n. Add the webhook URL from this workflow to your Facebook App/Webhook settings. AI Setup Add your Google Gemini API key (or swap for OpenAI/Claude). The included prompt is generic — you can edit it to match your brand tone. Optional Logging If you want to track processed messages, connect a Notion database or another CRM. How It Works Webhook catches new Facebook comments. AI Agent analyzes the comment and categorizes it (question, compliment, complaint, unclear, spam). Replying: For questions/requests → public reply + private message with full details. For compliments → short thank-you reply. For complaints → apology reply + private message for clarification. For unclear comments → ask politely if they need help. For spam/offensive → ignored (no reply). Replies and messages are sent instantly via the Facebook Graph API. Customization Ideas Change the AI prompt to match your brand voice. Add forwarding to Slack/Email if a human should review certain replies. Log conversations in Notion, Google Sheets, or a CRM for reporting. Expand to Instagram or WhatsApp with small adjustments. If you need any help Get In Touch

How it works User Signup & Verification: The workflow starts when a user signs up. It generates a verification code and sends it via SMS using Twilio. Code Validation: The user replies with the code. The workflow checks the code and, if valid, creates a session for the user. Conversational AI: Incoming SMS messages are analyzed by Chat GPT AI for sentiment, intent, and urgency. The workflow stores the conversation context and generates smart, AI-powered replies. Escalation Handling: If the AI detects urgency or frustration, the workflow escalates the session—alerting your team and sending a supportive SMS to the user. Set up steps Estimated setup time:** 10–20 minutes for most users. What you’ll need:** A free n8n account (self-hosted or cloud) Free Twilio account (for SMS) OpenAI API key (for AI) A PostgreSQL database (Supabase, Neon, or local) Setup process:** Import this workflow into n8n. Add your Twilio and OpenAI credentials as environment variables or n8n credentials. Update webhook URLs in your Twilio console (for incoming SMS). (Optional) Adjust sticky notes in the workflow for detailed, step-by-step guidance.

🚀 AI Marketing Campaign Generator Upload product image + details → Get complete professional marketing campaign with 5 custom-generated assets automatically. 🤖 AI Model GPT-4o Mini (OpenAI) - For campaign strategy | Prompt Image generation GPT Image-1 (OpenAI) - For visual asset generation 🔑 Required API Keys OpenAI API - AI analysis & image generation Google Drive API - Asset storage & organization 🎯 What It Generates 5 Marketing Assets: Instagram Post, Instagram Story, Website Banner, Ad Creative, Testimonial Graphic Brand Strategy: Colors, tone, positioning from your product image Campaign Strategy: Messaging, target audience, objectives Visual Analysis: Extracts colors, materials, styling from uploaded image ⚙️ Setup Import JSON to n8n Add OpenAI & Google Drive credentials Configure Google Drive folder for asset storage Deploy form webhook Test with product image upload 📱 How It Works Upload product image → AI analyzes visual + text → Generates complete campaign → Creates 5 custom marketing assets → Saves to Google Drive

Automating WhatsApp replies in Go High Level with Redis and Anthropic Description Integrates GHL + Wazzap with Redis and an AI Agent using ClientInfo to process messages, generate accurate replies, and send them via a custom field trigger. Who’s it for This workflow is for businesses using GoHighLevel (GHL), including the Wazzap plugin for WhatsApp, who want to automate inbound SMS/WhatsApp replies with AI. It’s ideal for teams that need accurate, data-driven responses from a predefined ClientInfo source and want to send them back to customers without paying for extra inbound automations. How it works / What it does Receive message in n8n via Webhook from GHL (Customer Replied (SMS) automation). WhatsApp messages arrive the same way using the Wazzap plugin. Filter message type: If audio → skip processing and send fallback asking for text. If text → sanitize by fixing escaped quotes, escaping line breaks/carriage returns/tabs, and removing invalid fields. Buffer messages in Redis to group multiple messages sent in a short window. Run AI Agent using the ClientInfo tool to answer only with accurate service/branch data. Sanitize AI output before sending back. Update GHL contact custom field (IA_answer) with the AI’s response. Send SMS reply automatically via GHL’s outbound automation triggered by the updated custom field. How to set up In GHL, create: Inbound automation: Trigger on Customer Replied (SMS) → Send to your n8n Webhook. Outbound automation: Trigger when IA_answer is updated → Send SMS to the contact. Create a custom field named IA_answer. Connect Wazzap in GHL to handle WhatsApp messages. Configure Redis in n8n (host, port, DB index, password). Add your AI model credentials (Anthropic, OpenAI, etc.) in n8n. (Optional) Set up the Google Drive Excel Merge sub-workflow to enrich ClientInfo with external data. Requirements GoHighLevel sub-account API key**. Anthropic (Claude)** API key or another supported LLM provider. Redis database** for temporary message storage. GHL automations: one for inbound messages to n8n, one for outbound replies when **IA\_answer is updated. GHL custom field: **IA\_answer to store and trigger replies. Wazzap plugin** in GHL for WhatsApp message handling. How to customize the workflow Add more context or business-specific data to the AI Agent prompt so replies match your brand tone and policies. Expand the ClientInfo dataset with additional services, branches, or product details. Adjust the Redis wait time to control how long the workflow buffers messages before replying.

VEXA: AI-Powered Meeting Intelligence I'll be honest, I built this because I was getting lazy in meetings and missing key details. I started with a simple VEXA integration for transcripts, then added AI to pull out summaries and tasks. But that just solved part of the problem. The real breakthrough came when we integrated Mem0, creating a persistent memory of every conversation. Now, you can stop taking notes and actually focus on the person you're talking to, knowing a system is tracking everything that matters. This is the playbook for how we built it. How It Works This isn't just one workflow; it's a two-part system designed to manage the entire meeting lifecycle from start to finish. Bot Management: It starts when you flick a switch in your CRM (Baserow). A command deploys or removes an AI bot from Google Meet. No fluff—it's there when you need it, gone when you don't. The workflow uses a quick "digital sticky note" in Redis to remember who the meeting is with and instantly updates the status in your Baserow table. AI Analysis & Memory: Once the meeting ends, VEXA sends the transcript over. Using the client ID (thank god for redis) , we feed the conversation to an AI model (OpenAI). It doesn't just summarize; it extracts actionable next steps and potential risks. All this structured data is then logged into a memory layer (Mem0), creating a permanent, searchable record of every client conversation. Setup Steps: Your Action Plan This is designed for rapid deployment. Here's what you do: Register Webhook: Run the manual trigger in the workflow once. This sends your n8n webhook URL to VEXA, telling it where to dump transcripts after a call. Connect Your CRM: Copy the vexa-start webhook URL from n8n. Paste it into your Baserow automation so it triggers when you set the "Send Bot" field to Start_Bot. Integrate Your Tools: Plug your VEXA, Mem0, Redis, and OpenAI API credentials into n8n. Use the Baserow Template: I've created a free Baserow template to act as your control panel. Grab it here: https://baserow.io/public/grid/t5kYjovKEHjNix2-6Rijk99y4SDeyQY4rmQISciC14w. It has all the fields you need to command the bot. Requirements An active n8n instance or cloud account. Accounts for VEXA.ai, Mem0.ai, Baserow, and OpenAI. A Redis database . Your Baserow table must have these fields: Meeting Link, Bot Name, Send Bot, and Status. Next Steps: Getting More ROI This workflow is the foundation. The real value comes from what you build on top of it. Automate Follow-ups:** Use the AI-identified next steps to automatically trigger follow-up emails or create tasks in your project management tool. Create a Unified Client Memory:** Connect your email and other communication platforms. Use Mem0 to parse and store every engagement, building a complete, holistic view of every client relationship. Build a Headless CRM:** Combine these workflows to build a fully AI-powered system that handles everything from lead capture to client management without any manual data entry. Copy the workflow and stop taking notes

📊 WEEX Spot Market Quant AI Agent (All-in-One Multi-Agent Trading System) ⚡ Overview This multi-agent n8n workflow delivers an automated, intelligent trading analysis system for the WEEX Spot Market. It uses GPT-4o to interpret user prompts, route them to the correct sub-agent tools, analyze technical indicators, price data, sentiment insights, and return concise trading signals via Telegram or downstream automations. No need to download additional workflows—everything is embedded in this single orchestrated agent. 🧠 Core Features 🔹 Single-entry architecture → Built-in orchestration logic with no external subworkflow dependencies 🔹 Multi-timeframe indicator analysis → 15m, 1h, 4h, and 1d 🔹 Sentiment + news insights from crypto sources 🔹 Live price, volume, kline, and order book analysis 🔹 LLM-powered signal evaluation using GPT-4o 🔹 Telegram integration for fast human queries or autonomous alerts 🤖 Built-In Agent Modules | Module | Description | | ----------------------------------- | ---------------------------------------------------------- | | ✅ Financial Analyst Tool | Routes prompts, interprets tokens, and triggers sub-agents | | ✅ News & Sentiment Analyst Tool | Gathers real-time sentiment from crypto news sources | | ✅ Technical Indicator Tools | 15m, 1h, 4h, 1d indicators using WEEX spot market data | | ✅ Price & Order Book Agent | Fetches real-time stats, price, and structure | | ✅ Trading Signal Evaluator | GPT-4o merges all data and generates trading decision | 🖥️ Prompt Flow Example User Input: “Should I long or short ETH on WEEX today?” → Financial Analyst Agent interprets the query → Fetches multi-timeframe indicators, live price, sentiment → GPT-4o evaluates conditions and creates recommendation → Output delivered via Telegram: 📈 ETH/USDT Overview • Price: \$3,710 • 4h RSI: 64.5 – Slightly Overbought • MACD: Bullish Crossover • Market Sentiment: 🔼 Positive Recommendation: Consider long entry with stop at \$3,640. 🔧 Setup Instructions Follow these steps to fully deploy and operate the WEEX Quant AI Agent in your n8n environment: 🟢 Get Telegram Bot API Key Create your bot via @BotFather on Telegram Save the token it gives you (format: 123456789:ABCdefGHIjkLMNopQRStuvWXyz) 🔑 Add OpenAI / DeepSeek Chat API Key Compatible with GPT-4o (OpenAI) or DeepSeek Chat 📈 (Optional) WEEX API Keys If expanding to live trading or authenticated data, get a WEEX Spot API key from your account dashboard Not required for the analysis agent to function 🔗 Connect Telegram to n8n Use Telegram Trigger and Telegram node with your API key Ensure webhook is set correctly (or use polling mode) ✅ Example Use Cases | Scenario | Outcome | | ---------------------------------- | ----------------------------------------------------- | | “Is BTC bullish or bearish?” | Merged indicator + sentiment + price analysis summary | | “Get 15m and 4h trends for SOL” | Multi-timeframe volatility vs macro trend report | | “Latest crypto news on XRP” | Real-time filtered news + DeepSeek sentiment summary | | “What’s the order book structure?” | Level-by-level spread analysis with buy/sell volumes | 🎥 Watch the Live Demo 👨‍💼 Licensing & Support 🧾 © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade signal framework are IP-protected. No unauthorized rebranding or replication permitted. 📩 Connect with the Creator Don Jayamaha – LinkedIn Profile

How it Works This workflow lets you build a Messenger AI Agent capable of understanding text, images, and voice notes, and replying intelligently in real time. It starts by receiving messages from a Facebook Page via a Webhook, detects the message type (text, image, or audio), and routes it through the right branch. Each input is then prepared as a prompt and sent to an AI Agent that can respond using text generation, perform quick calculations, or fetch information from Wikipedia. Finally, the answer is formatted and sent back to Messenger via the Graph API, creating a smooth, fully automated chat experience. Set Up Steps Connect credentials Add your OpenAI API key and Facebook Page Access Token in n8n credentials. Plug the webhook Copy the Messenger webhook URL from your workflow and paste it into your Facebook Page Developer settings (Webhook → Messages → Subscribe). Customize the agent Edit the System Message of the AI Agent to define tone, temperature, and purpose (e.g. “customer support”, “math assistant”). Enable memory & tools Turn on Simple Memory to keep conversation context and activate tools like Calculator or Wikipedia. Test & deploy Switch to production mode, test text, image, and voice messages directly from Messenger. Benefits 💬 Multi-modal Understanding — Handles text, images, and audio messages seamlessly. ⚙️ Full Automation — End-to-end workflow from Messenger to AI and back. 🧠 Smart Replies — Uses OpenAI + Wikipedia + Calculator for context-aware answers. 🚀 No-Code Setup — Build your first Messenger AI in less than 30 minutes. 🔗 Extensible — Easily connect more tools or APIs like Airtable, Google Sheets, or Notion.

Automate Bug Reports: GitHub Issues → AI Analysis → Jira Tickets with Slack & Discord Alerts Automatically convert GitHub issues into analyzed Jira tickets with AI-powered severity detection, developer assignment, and instant team alerts. Overview This workflow captures GitHub issues in real-time, analyzes them with GPT-4o for severity and categorization, creates enriched Jira tickets, assigns the right developers, and notifies your team across Slack and Discord—all automatically. Features AI-Powered Triage**: GPT-4o analyzes bug severity, category, root cause, and generates reproduction steps Smart Assignment**: Automatically assigns developers based on mentioned files and issue context Two-Way Sync**: Posts Jira ticket links back to GitHub issues Multi-Channel Alerts**: Rich notifications in Slack and Discord with action buttons Time Savings**: Eliminates 15-30 minutes of manual triage per bug Customizable Routing**: Easy developer mapping and priority rules What Gets Created Jira Ticket: Original GitHub issue details with reporter info AI severity assessment and categorization Reproduction steps and root cause analysis Estimated completion time Automatic labeling and priority assignment GitHub Comment: Jira ticket link AI analysis summary Assigned developer and estimated time Team Notifications: Severity badges and quick-access buttons Developer assignment and root cause summary Color-coded priority indicators Use Cases Development teams managing 10+ bugs per week Open source projects handling community reports DevOps teams tracking infrastructure issues QA teams coordinating with developers Product teams monitoring user-reported bugs Setup Requirements Required: GitHub repository with admin access Jira Software workspace OpenAI API key (GPT-4o access) Slack workspace OR Discord server Customization Needed: Update developer email mappings in "Parse GPT Response & Map Data" node Replace YOUR_JIRA_PROJECT_KEY with your project key Update Slack channel name (default: dev-alerts) Replace YOUR_DISCORD_WEBHOOK_URL with your webhook Change your-company.atlassian.net to your Jira URL Setup Time: 15-20 minutes Configuration Steps Import workflow JSON into n8n Add credentials: GitHub OAuth2, Jira API, OpenAI API, Slack, Discord Configure GitHub webhook in repository settings Customize developer mappings and project settings Test with sample GitHub issue Activate workflow Expected Results 90% faster bug triage (20 min → 2 min per issue) 100% consistency in bug analysis Zero missed notifications Better developer allocation Improved bug documentation Tags GitHub, Jira, AI, GPT-4, Bug Tracking, DevOps, Automation, Slack, Discord, Issue Management, Development, Project Management, OpenAI, Webhook, Team Collaboration

How it works Your WhatsApp AI Assistant automatically handles customer inquiries by linking your Google Docs knowledge base to incoming WhatsApp messages. The system instantly processes customer questions, references your business documentation, and delivers AI-powered responses through OpenAI or Gemini - all without you lifting a finger. Works seamlessly in individual chats and WhatsApp groups where the assistant can respond on your behalf. Set up steps Time to complete: 15-30 minutes Step 1: Create your WhapAround account and connect your WhatsApp number (5 minutes) Step 2: Prepare your Google Doc with business information and add the document ID to the system (5 minutes) Step 3: Configure the WhatsApp webhook and map message fields (10 minutes) Step 4: Connect your OpenAI or Gemini API key (3 minutes) Step 5: Send a test message to verify everything works (2 minutes) Optional: Set up PostgreSQL database for conversation memory and configure custom branding/escalation rules (additional 15-20 minutes) Detailed technical configurations, webhook URLs, and API parameter settings are provided within each workflow step to guide you through the exact setup process.