HTTP Request and WhatsApp Business Cloud integration

📱🤖 Create Stunning AI Images Directly from WhatsApp with Gemini This workflow transforms your WhatsApp into a personal AI image generation studio. Simply send a text message with your idea, and this bot will use the advanced prompt engineering capabilities of Gemini 2.5 Pro to craft a detailed, artistic prompt. It then uses Gemini 2.0 Flash to generate a high-quality image from that prompt and sends it right back to your chat. It's a powerful yet simple way to bring your creative ideas to life, all from the convenience of your favorite messaging app\! What this workflow does Listens for WhatsApp Messages: The workflow starts automatically when you send a message to your connected WhatsApp number. Enhances Your Idea with AI: It takes your basic text (e.g., "a knight on a horse") and uses Gemini 2.5 Pro to expand it into a rich, detailed prompt perfect for image generation (e.g., "A cinematic, full-body shot of a stoic knight in gleaming, ornate silver armor, riding a powerful black warhorse through a misty, ancient forest. The scene is lit by ethereal morning sunbeams piercing the canopy, creating dramatic volumetric lighting and long shadows. Photorealistic, 8K, ultra-detailed, award-winning fantasy concept art."). Generates a Unique Image: It sends this enhanced prompt to the Google Gemini 2.0 Flash image generation API. Prepares the Image: The API returns the image in Base64 format, and the workflow instantly converts it into a binary file. Sends it Back to You: The final, high-quality image is sent directly back to you in the same WhatsApp chat. Nodes Used 🟢 WhatsApp Trigger: The entry point that listens for incoming messages. 🧠 LangChain Chain (LLM): Uses Gemini 2.5 Pro for advanced prompt engineering. ➡️ HTTP Request: Calls the Google Gemini 2.0 Flash API to generate the image. 🔄 Convert to File: Converts the Base64 image data into a sendable file format. 💬 WhatsApp: Sends the final image back to the user. Prerequisites To use this workflow, you will need: An n8n instance. A WhatsApp Business Account connected to n8n. You can find instructions on how to set this up in the n8n docs. A Google Gemini API Key. You can get one for free from Google AI Studio. How to use this workflow Get your Google Gemini API Key: Visit the Google AI Studio and create a new API key. Configure the Gemini 2.5 Pro Node: In the n8n workflow, select the Gemini 2.5 Pro node. Under 'Connect your account', click 'Create New' to add a new credential. Paste your Gemini API key from the previous step and save. Configure the Generate Image (HTTP Request) Node: Select the Generate Image node. In the properties panel on the right, find the Query Parameters section. In the 'Value' field for the key parameter, replace "Your API Key" with your actual Google Gemini API Key. Connect WhatsApp: Select the WhatsApp Trigger node. Follow the instructions to connect your WhatsApp Business Account credential. If you haven't created one, the node will guide you through the process. Activate and Test: Save the workflow using the button at the top right. Activate the workflow using the toggle switch. Send a message to your connected WhatsApp number (e.g., "A futuristic city in the style of Van Gogh"). The bot will process your request and send a stunning AI-generated image right back to you\!

WhatsApp AI Agent: Auto-Train Product Data & Handle Customer Support Who Is This For This workflow is ideal for eCommerce founders, product managers, customer support teams, and automation builders who rely on WhatsApp to manage product information and interact with clients. It’s perfect for businesses that want to automate product data entry and support responses directly from WhatsApp messages using GPT-4 and Google Sheets. What Problem Does This Workflow Solve Manual Product Data Entry**: Collecting and organizing product data from links is tedious and error-prone. Slow Customer Response Times**: Responding to client questions manually leads to delays and inconsistent support. No Logging System for Issues**: Without automation, support issues often go undocumented, making it harder to learn and improve. What This Workflow Does Step 1 – Incoming Message Detection Listens for incoming messages via WhatsApp. If the message starts with train:, it routes to the product training process. Otherwise, it routes to the customer support assistant. Step 2 – Product Data Training Extracts URL** from the message using a regex script. Fetches HTML content** from the URL. Cleans HTML data** to extract readable product description. Saves raw data** (URL + description) into Google Sheets. Uses GPT-4** to enhance product data: → Name, price (one-time or subscription), topic, and FAQs. Updates the product row** in Google Sheets with structured information. Step 3 – Customer Support Flow Analyzes user messages with GPT-4 to understand the request or issue. Looks up relevant product info in Google Sheets. Detects potential problems (e.g. payment, login, delivery). Suggests an appropriate solution. Logs the problem, solution, and category to the Customer Issues sheet. Sends a response back to the client via WhatsApp. Step 4 – Client Response Sends the AI-generated response to the client via WhatsApp. Keeps the communication fast, clear, and professional. Setup Guide Prerequisites WhatsApp Business API access** OpenAI API Key** Google Account** with Google Sheets access A hosted instance of n8n (Cloud or self-hosted) Setup Steps Import the Workflow into your n8n instance. Connect your credentials for WhatsApp, OpenAI, and Google Sheets. Customize Google Sheet IDs and names as needed. Test by sending a train: message or a regular customer message to WhatsApp. Activate the workflow to make it live. How to Customize This Workflow Edit AI prompts** to reflect your product type, language style, or tone. Change the trigger keyword** (e.g. from train: to add: or anything else). Add integrations** like Notion, Airtable, or CRM tools. Expand the Sheets structure** with more product fields (e.g. stock status, image link). Add notifications** to Slack or email after product updates or issue logging. 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube

How it works • Transcribes a WhatsApp voice or text message from a prospect using Whisper or GPT • Extracts key information (name, need, context, urgency) via AI • Matches the most relevant service pack by comparing the prospect’s need with Airtable data • Dynamically fills a branded template via APITEMPLATE (HTML or PDF) • Generates a clean, personalized business proposal — including dynamic links (payment, calendar, etc.) • Sends the final PDF back instantly via WhatsApp or email Set up steps • ⏱ Estimated setup time: 45–60 minutes • ✅ You’ll need:  ◦ WhatsApp Business Cloud API access (with webhook configured)  ◦ OpenAI API key (Whisper + GPT)  ◦ Airtable (to store service packs and client input)  ◦ APITEMPLATE account (template with placeholders like {{nom}}, {{prix}}, {{lien_reservation}}, etc.)  ◦ n8n instance (cloud or self-hosted) • 📦 Create your service packs in Airtable with associated links (Stripe, Calendly…) • 🔗 The proposal auto-includes these links dynamically inside the PDF • 🚀 Workflow orchestrates the end-to-end process: from WhatsApp input to PDF delivery

The Magento 2 Smart Maintenance AI Agent revolutionises how you interact with your store’s backend — allowing you to safely run critical maintenance and cache operations using plain natural language via Telegram or WhatsApp. ❗ The Problem Magento store issues never wait for office hours. Caches fill up, indexes break, or maintenance mode gets stuck — usually late at night, during weekends, or right before a campaign launch. Most store owners can’t fix these on their own and must wait for a developer or agency response, causing lost sales, downtime, and stress. 💡 The Solution The Magento 2 Smart Maintenance AI Agent acts as your personal, always-on rescue assistant. It turns your Telegram or WhatsApp chat into a command center — where you can say: “Please clear cache” “Disable maintenance mode” “Reindex catalog search” and instantly receive the correct, safe Magento CLI command. No SSH logins, no technical knowledge, no risk and no long wait chasing developer team. It’s your Magento First-Aid Kit — ready anytime, anywhere — that never runs dangerous commands like setup:upgrade or deploy. More messages like: “please clear full page cache” “reindex catalog search” “enable maintenance mode” “check if my site is under maintenance” and this AI-driven n8n workflow will instantly translate it into the correct and safe bin/magento command, while automatically blocking any risky operations (like setup or deployment). This template empowers developers, agencies, and support teams to manage Magento stores from anywhere — safely, intelligently, and conversationally. 🔍 What It Does: Interprets natural language into Magento CLI commands Supports Telegram and WhatsApp message interfaces Automatically identifies parameters like cache type or indexer name “Clear full page cache” → bin/magento cache:clean full_page “Reindex catalog search” → bin/magento indexer:reindex catalogsearch_fulltext Detects unsafe commands (like setup:upgrade) and returns a warning message Provides fully formatted, Telegram-safe output (no entity parsing errors) Can be integrated with Execute Command, SSH, or Magento APIs for real automation ⚙️ Technical Highlights: Powered by the n8n AI Agent Node (OpenAI or compatible LLM) Smart System Message Prompt ensures strict command safety Natural Language Understanding (NLU) for cache/index type recognition Compatible with Telegram Bot and WhatsApp Cloud API Outputs single-line CLI commands (safe for live chat or automation execution) Modular flow — extendable with triggers, schedulers, or approval gates ✅ Ideal For: Magento 2 developers and DevOps engineers Managed service providers and agencies Support or hosting teams maintaining multiple Magento stores Technical managers wanting safe control via chat eCommerce automation enthusiasts 📈 Why This Matters in the Current Market: As teams move toward AI-driven DevOps, eCommerce maintenance needs to keep pace. Magento remains one of the most powerful yet complex systems — and manual CLI management can be error-prone, slow, and risky. This AI Agent enables: Instant control via Telegram or WhatsApp Production safety through command filtering Parameter intelligence (cache and index targeting) Modern DevOps efficiency via conversational AI 🔧 Modules Used: AI Agent Node (OpenAI / GPT-compatible) Telegram Node WhatsApp Node Function Node Response Formatter Node 💼 Use Cases: Run safe Magento maintenance commands from Telegram or WhatsApp Let your DevOps team trigger safe CLI operations remotely Automate after-hours store operations via chat commands Integrate with monitoring workflows to self-heal caches or reindex automatically Use AI as a conversational Magento control interface 🔒 Credentials Required: OpenAI API Key (or equivalent LLM key) Telegram Bot API Token (for Telegram) WhatsApp Cloud API Credentials (optional, for WhatsApp integration) (Optional) Server credentials for local execution of CLI commands 📂 Category 🧠 AI Agents / 🛒 eCommerce / ⚙️ DevOps Automation / 💬 ChatOps Contact: Author 👤 Author Kanaka Kishore Kandregula Certified Magento 2 Developer https://gravatar.com/kmyprojects https://www.linkedin.com/in/kanakakishore

🔍 How it works This workflow turns WhatsApp into a smart email command center using AI. Users can speak or type instructions like: "Send a follow-up to Claire” "Write a draft email to Claire to confirm tomorrow’s meeting at 5 PM” "What is the name of Claire's firm?” The agent transcribes voice notes, extracts intent with GPT, interacts with Gmail (send, draft, search), and replies with a confirmation via WhatsApp — either as text or a voice message. ⚙️ Key Modules Used WhatsApp Business Webhook (Meta) OpenAI Whisper (voice transcription) GPT (intent + content generation) Gmail (search, draft, send) Airtable (contact lookup + memory logging) 🧠 Memory Layer (Optional) The agent logs key fields in Airtable: Recipient email Company / job title And more... This creates a lightweight "gut memory” so the agent feels context-aware. 🗺️ Setup Steps Connect WhatsApp Business API (via Meta Developer Console) Add OpenAI and Gmail credentials in n8n Link your Airtable base for contacts and logging 🧩 Best Use Cases Hands-free email reply while commuting Fast Gmail access for busy consultants / solopreneurs Custom business agents for service-based professionals ⏱️ Estimated Setup Time 30–60 minutes ✅ Requirements WhatsApp Business Cloud access OpenAI API Key Gmail or Google Workspace Airtable account (free plan OK) n8n instance (cloud or self-hosted with HTTPS)

This workflow automates multi-channel AI-driven sales engagement for lead qualification, service information delivery, and consultation booking. It integrates WhatsApp, Facebook Messenger, Instagram DM, and an n8n chat interface with a backend CRM (Airtable), a knowledge base (Supabase), and conversational AI (OpenAI), all orchestrated by n8n. Tools & Services Used Messaging Platforms: WhatsApp, Facebook Messenger, Instagram DM, n8n Built-in Chat AI Core & Processing: OpenAI (GPT-4o for main agent logic, Whisper for audio transcription) CRM & Data Management: Airtable (for initial WhatsApp lead lookup, lead form submissions, and as the backend for the crmAgent sub-workflow operations) Knowledge Base: Supabase (Vector Store for technical_and_sales_knowledge tool) Chat Memory: PostgreSQL (for the main AI Agent's conversation history) Orchestration & Automation: n8n (Self-hosted, utilizing Langchain community nodes) Calendar Service: Integrated via the calendarAgent sub-workflow CRM Service: Integrated via the crmAgent sub-workflow (interacting with Airtable) Workflow Overview This automation performs the following steps: Trigger: A new interaction is initiated through one of the following channels: A new message is received via the WhatsApp Trigger. A new message is received via the Facebook Trigger (Webhook). A new message is received via the Instagram Trigger (Webhook). A new message is received via the n8n Chat Trigger. Alternatively, a new lead is submitted via the Airtable Form Submitted Webhook. Channel-Specific Ingestion & Pre-processing: For WhatsApp: The system attempts to find an existing lead in Airtable using the sender's phone number. Incoming messages are routed by the Handle Message Types switch: Text messages are passed to the Edit Fields - chat1 node to prepare input for the AI Agent, including any found lead information. Audio messages are processed: the WhatsApp Business Cloud node gets the media URL, the HTTP Request node downloads the audio, OpenAI transcribes it to text, and Edit Fields - chat2 prepares this transcribed text and lead information for the AI Agent. Unsupported message types trigger the Reply To User1 node to send a notification that the message type cannot be processed. For Facebook Messenger: The system responds to webhook verification (Respond to Webhook - facebook get) and acknowledges new messages (Respond to Webhook - facebook post). The If is not echo - facebook node filters out messages sent by the page. The Sales Agent Demo - typing_on node sends a typing indicator. The Edit Fields - facebook node prepares the message text, sender ID, and Facebook-specific context for the AI Agent. For Instagram DM: The system responds to webhook verification (Respond to Webhook - instagram get) and acknowledges new messages (Respond to Webhook - instagram post). The If is not echo - instagram node filters out messages sent by the business account. The Edit Fields - instagram node prepares the message text, sender ID, and Instagram-specific context for the AI Agent. For n8n Chat: The Edit Fields - chat node prepares the user's input and session information for the AI Agent. Input Aggregation for AI Agent: Processed data from all active messaging channels (WhatsApp text/audio, Facebook, Instagram, n8n Chat) is funneled through the No Operation, do nothing node to the main AI Agent. AI Sales Conversation & Tool Utilization: The AI Agent (using OpenAI Chat Model - GPT-4o, and Postgres Chat Memory) engages the user according to its system prompt, aiming to qualify them for Paint Protection Film (PPF), Ceramic Coating, or Window Tint. The AI Agent uses the technical_and_sales_knowledge tool (which queries the Demo Supabase vector store via Embeddings OpenAI and OpenAI Chat Model1) to provide service details and answer questions. The AI Agent uses the crmAgent tool (a sub-workflow) to log contact details (Name, Email, service interest) and update opportunity statuses in Airtable. The AI Agent uses the calendarAgent tool (a sub-workflow) to book consultation appointments once preferred dates/times are provided. This occurs after contact details are logged in the CRM. Response Delivery: The AI Agent's final textual response is passed to the Switch node. The Switch node routes the response to the appropriate node for delivery on the original channel: Reply To User for WhatsApp. Facebook Graph API - Sales Agent Demo for Facebook Messenger. Instagram Graph API - smb.sales.agent.demo for Instagram DM. Output - chat for the n8n Chat interface. Airtable Form Submission Processing (Separate Branch): When the Airtable Form Submitted webhook receives data, the Airtable node fetches the full record. The Create Contact node creates a new contact in the Airtable 'Contacts' table. The Edit Fields - form node prepares data for a notification. The WhatsApp Business Cloud2 node sends a templated WhatsApp message to the lead, confirming their form submission.

The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot. How it works: Webhook Setup: The workflow begins by setting up webhooks for verification and response. The Verify webhook receives GET requests and sends back a verification code, while the Respond webhook handles incoming POST requests from Meta regarding WhatsApp messages. Message Handling: Once a message is received, the workflow checks if the incoming JSON contains a user message. If it does, the message is processed further; otherwise, a generic response is sent. AI Agent Interaction: The user's message is passed to the AI Agent node, which uses a conversational agent with a predefined system message tailored for an electronics store. This ensures that the AI provides accurate and professional responses based on the knowledge base. Knowledge Base Utilization: The AI Agent references a knowledge base stored in Qdrant, a vector database. Documents from Google Drive are downloaded, vectorized using OpenAI embeddings, and stored in Qdrant for retrieval during conversations. Response Generation: The AI Agent generates a response using the OpenAI chat model (gpt-4o-mini) and sends it back to the user via WhatsApp. Set up steps: Create Qdrant Collection: Update the QDRANTURL and COLLECTION variables in the workflow. Use the Create collection HTTP request node to initialize the collection in Qdrant. Vectorize Documents: Configure the Get folder and Download Files nodes to fetch documents from a specified Google Drive folder. Use the Embeddings OpenAI node to generate embeddings for the downloaded files. Store the vectorized documents in Qdrant using the Qdrant Vector Store node. Configure Webhooks: Ensure both Verify and Respond webhooks have the same URL. Set the Verify webhook to use the GET HTTP method and the Respond webhook to use the POST HTTP method. Set Up AI Agent: Define the system prompt for the AI Agent, specifying guidelines for product information, technical support, customer service, and knowledge base usage. Link the AI Agent to the OpenAI chat model and configure any additional tools as needed. Test Workflow: Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all components are functioning correctly. Monitor the flow of data through the nodes and verify that responses are being generated and sent accurately. By following these steps, the workflow will be fully operational, enabling a robust AI-powered chatbot capable of handling customer inquiries via WhatsApp. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case! How it works Incoming WhatsApp Trigger provides a way to get messages into the workflow. The message received is extracted and sent through 1 of 4 branches for processing. Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video. The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries. Finally, the response message is sent back to the WhatsApp user using the WhatsApp node. How to use Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages. Good to know: Large media files may negatively impact workflow performance. Requirements WhatsApp Buisness account Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not. Customising this workflow For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better. Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!

How It Works Top Branch Workflow* The Data Scientist: Ingest: Pulls historical sales data from Google Sheets. Math Engine: Runs 7 statistical algorithms (e.g., Seasonal Naive, Linear Trend, Regression). It backtests them against your history and scientifically selects the winner with the lowest error rate. The Data Analyst: Interpret: The AI Agent takes the mathematical output and translates it into business insights, assigning confidence scores based on error margins. Report: Generates a visual trend chart (PNG) and sends a complete briefing to your phone. Bottom Branch Workflow* The Consultant: AI Agent 2 handles the follow-up questions. It pulls the latest analysis context and checks historical rate data to give an informed answer. Recall: When you ask a question via WhatsApp, the bot retrieves the saved forecast state. Answer: It acts as an on-demand analyst, comparing current forecasts against historical actuals to give you instant answers. Setup Steps 1) Google Sheet: Prepare columns: Year, Month, Sales. Map the Sheet ID in the "Workflow Configuration" node. 2) Forecast Engine: No config needed. It automatically detects seasonality vs. linear trends. 3) Database: Create a table latest_forecast to store the JSON output. 4) Credentials: Connect Google Sheets, OpenAI, and WhatsApp Use Cases & Benefits For Business Owners: Gain enterprise-grade forecasting on autopilot. Always have a sophisticated financial outlook running in the background 24/7. For Sales Leaders: Get immediate visibility into future revenue trends. Bypass the wait for end-of-month manual reports and get a strategic "pulse check" delivered instantly to your phone. 🤖Virtual Data Team: Instantly add the capabilities of a Data Scientist and Data Analyst to your business or division. It works alongside your existing team to handle the heavy lifting, or stands in as your dedicated automated department. 🧠Precision & Trust: Combines the best of both worlds: rigorous, deterministic code for the math (no hallucinations) and advanced AI for the strategic explanation. You get numbers you can trust with context you can use. ⚡Decision-Ready Insights: Stop digging through dashboards. High-level intelligence is pushed directly to you on WhatsApp, allowing you to make faster, data-driven decisions from anywhere. 📬 Want to Customize This? [email protected]

How It Works This workflow transforms any webpage into an AI-narrated audio summary delivered via WhatsApp: Receive URL - WhatsApp Trigger captures incoming messages and passes them to URL extraction Extract & validate - Code node extracts URLs using regex and validates format; IF node checks for errors User feedback - Sends either error message ("Please send valid URL") or processing status ("Fetching and analyzing... 10-30 seconds") Fetch webpage - Sub-workflow calls Jina AI Reader (https://r.jina.ai/) to fetch JavaScript-rendered content, bypassing bot blocks Summarize content - GPT-4o-mini processes webpage text in 6000-character chunks, extracts title and generates concise summary Generate audio - OpenAI TTS-1 converts summary text to natural-sounding audio (Opus format for WhatsApp compatibility) Deliver result - WhatsApp node sends audio message back to user with summary Why Jina AI? Many modern websites (like digibyte.io) require JavaScript to load content. Standard HTTP requests only fetch the initial HTML skeleton ("JavaScript must be enabled"). Jina AI executes JavaScript and returns clean, readable text. Setup Steps Time estimate: ~20-25 minutes WhatsApp Business API Setup (10-15 minutes) Create Meta Developer App** - Go to https://developers.facebook.com/, create Business app, add WhatsApp product Get Phone Number ID** - Use Meta's test number or register your own business phone Generate System User Token** - Create at https://business.facebook.com/latest/settings/system_users (permanent token, no 4-hour expiry) Configure Webhook** - Point to your n8n instance URL, subscribe to "messages" events Verify business** - Meta requires 3-5 verification steps (business, app, phone, system user) Configure n8n Credentials (5 minutes) OpenAI** - Add API key in Credentials → OpenAI (used in 2 places: "Convert Summary to Audio" and "OpenAI Chat Model" in sub-workflow) WhatsApp OAuth** - Add in WhatsApp Trigger node using System User token from step 1 WhatsApp API** - Add in all WhatsApp action nodes (Send Error, Send Processing, Send Audio) using same token Link Sub-Workflow (3 minutes) Ensure "[SUB] Get Webpage Summary" workflow is activated In "Get Webpage Summary" node, select the sub-workflow from dropdown Verify workflow ID matches: QglZjvjdZ16BisPN Update Phone Number IDs (2 minutes) Copy your Phone Number ID from Meta console Update in all WhatsApp nodes: Send Error Message, Send Processing Message, Send Audio Summary Test the Flow (2 minutes) Activate both workflows (sub-workflow first, then main) Send test message to WhatsApp: https://example.com Verify: Processing message arrives → Audio summary delivered within 30 seconds Important Notes WhatsApp Caveats: 24-hour window** - Can't auto-message users after 24 hours unless they message first (send "Hi" each morning to reset) Verification fatigue** - Meta requires multiple business verifications; budget 30-60 minutes if first time Test vs Production** - Test numbers work for single users; production requires business verification Audio Format: Using Opus codec (optimal for WhatsApp, smaller file size than MP3) Speed set to 1.0 (normal pace) - adjust in "Convert Summary to Audio" node if needed Cost: ~$0.015 per minute of audio generated Jina AI Integration: Free tier** works for basic use (no API key required) Handles JavaScript-heavy sites automatically Add Authorization: Bearer YOUR_KEY header for higher limits Alternative: Replace with Playwright/Puppeteer for self-hosted rendering Cost Breakdown (per summary): GPT-4o-mini summarization: ~$0.005-0.015 OpenAI TTS audio: ~$0.005-0.015 WhatsApp messages: Free (up to 1,000/month) Total: ~$0.01-0.03 per summary** Troubleshooting: "Cannot read properties of undefined" → Status update, not message (code node returns null correctly) "JavaScript must be enabled" → Website needs Jina AI (already implemented in Fetch site texts node) Audio not sending → Check binary data field is named data in TTS node No webhook received → Verify n8n URL is publicly accessible and webhook subscription includes "messages" Pro Tips: Change voice in TTS node: alloy (neutral), echo (male), nova (female), shimmer (soft) Adjust summary length: Modify chunkSize: 6000 in sub-workflow's Text Splitter node (lower = faster but less detailed) Add rate limiting: Insert Code node after trigger to track user requests per hour Store summaries: Add database node after "Clean up" to archive for later retrieval The Use Cases: Executive commuting - Consume industry news hands-free Research students - Cover 3x more sources while multitasking Visually impaired - Access any webpage via natural audio Sales teams - Research prospects on the go Content creators - Monitor competitors while exercising

Overview This project is an AI-powered WhatsApp virtual agent built using n8n, designed to handle both text and voice-based customer messages automatically. The workflow integrates Google Gemini, Pinecone, and the WhatsApp Business API to provide intelligent, context-aware responses that feel natural and professional. How It Works Message Detection The workflow begins when a message arrives on WhatsApp. It identifies whether the message is text or voice and routes it accordingly. Voice Message Handling Audio messages are securely downloaded from WhatsApp. The files are converted to Base64 format and sent to the Gemini API for transcription. The transcribed text is then passed to the AI Agent for further processing. AI Agent Processing The LangChain AI Agent acts as the brain of the system. It uses: Google Gemini Chat Model** for natural language understanding and response generation. Pinecone Vector Store** to retrieve company-specific information and product data. Memory Buffer** to remember the last 20 user messages, ensuring context-aware responses. The agent also follows a set of custom communication rules — replying only in approved languages, skipping greetings, and focusing on direct, helpful, and professional responses (e.g., product recommendations, support, or guidance). Knowledge Retrieval The AI Agent connects to a Pinecone database containing detailed company data, such as product catalogs or service FAQs. Using Gemini-generated embeddings, it retrieves the most relevant information for each user query. Response Delivery Once the AI Agent prepares the response, it is instantly sent back to the user via WhatsApp, completing the conversational loop. Who It’s For This system is ideal for businesses seeking to automate their customer communication through WhatsApp. It’s especially valuable for: Product-based companies** with frequent customer inquiries. Service providers** offering 24/7 customer assistance or quote requests. SMBs** looking to scale their communication without hiring additional staff. Tech Stack & Requirements n8n** – Workflow automation and orchestration. WhatsApp Cloud API** – For sending and receiving messages. Google Gemini (PaLM)** – For LLM-based transcription and response generation. Pinecone** – Vector database for product and service knowledge retrieval. LangChain Integration** – For connecting memory, vector store, and reasoning tools. Custom Business Rules** – Configurable within the AI Agent node to manage tone, style, and workflow behavior. Key Features Handles both text and voice messages seamlessly. Responds in multiple languages, including English. Maintains conversation memory per user session. Retrieves accurate company-specific information using vector search. Fully automated, with customizable behavior for different industries or use cases. Setup Instructions Prerequisites Before importing the workflow, ensure you have: An active n8n instance (self-hosted or n8n Cloud). WhatsApp Cloud API credentials** from Meta. Google Gemini API key** with model access (for chat and transcription). Pinecone API key** with a preconfigured vector index containing your company data. Environment Setup Install all required credentials under Settings → Credentials in n8n. Add environment variables (if applicable) for keys like: GOOGLE_API_KEY=your_google_gemini_key PINECONE_API_KEY=your_pinecone_key WHATSAPP_ACCESS_TOKEN=your_whatsapp_token Pinecone Configuration Create a Pinecone index named, for example, products-index. Upload company documents or product details as vector embeddings using Gemini or LangChain utilities. Adjust the retrieval limit in the Pinecone node settings for broader or narrower search responses. WhatsApp API Configuration Set up a WhatsApp Business Account via Meta Developer Dashboard. Create a webhook endpoint URL (n8n’s public URL) to receive WhatsApp messages. Use the WhatsApp Trigger Node to capture messages in real time. AI Agent Customization You can personalize how the AI behaves by editing the system prompt inside the AI Agent node: Modify tone, response length, or product focus. Add new “rules” for language preferences or conversation flow. Include links or custom text output (e.g., quotation formats, product catalog messages). Handling Voice Messages Ensure your WhatsApp Business Account has media message permissions enabled. Verify the HTTP Request node that connects to the Gemini API for transcription is correctly authenticated. You can adjust the transcription model or prompt if you prefer shorter, keyword-based outputs. Testing Send both text and voice messages from a test WhatsApp number. Check response time and message formatting. Use n8n’s execution logs to debug errors (especially for media downloads or API credentials). Customization Options 🧩 AI Behavior Modify the AI Agent’s system message to adapt tone and personality (e.g., sales-oriented, support-driven). Update memory length (default: last 20 messages) for longer or shorter conversations. 🌍 Multi-language Support Add or remove allowed languages in the rules section of the AI Agent node. For multilingual businesses, duplicate the AI Agent path and route messages by language detection. 📦 Industry Adaptation Swap the Pinecone dataset to suit different industries — retail, hospitality, logistics, etc. Replace product data with FAQs, customer records, or support documentation.

🚀 TikTok Video Automation Tool ✨ (Frequent Updates) Create viral TikTok videos effortlessly — no editing skills required! Who is this for? 🎯 ✅ Content Creators: Pump out engaging short videos in minutes. ✅ Marketing Agencies: Deliver high-quality client content — fast. ✅ Business Owners: Promote your brand with attention-grabbing TikToks. What problem does this solve? 🛠️ Short-form video content is king, but creating it takes time, skill, and effort. This tool automates the entire process, from scriptwriting to video production, ensuring SEO-optimized, high-quality content without any manual editing. How it works 🌟 1️⃣ Enter your video idea and choose where to receive the final video (TikTok upload or link via WhatsApp, Gmail, etc.). 2️⃣ AI crafts a high-engagement script with SEO optimization. 3️⃣ Voiceover is generated with ultra-realistic AI narration. 4️⃣ Relevant visuals are selected to perfectly match the script. 5️⃣ Your TikTok video is assembled and either directly uploaded to TikTok or delivered via a shareable link. Quick & Easy Setup ⚙️ (5-10 min) 🔹 Connect required APIs (most have free plans). 🔹 Follow the step-by-step setup (video tutorial included). 🔹 Start generating professional TikTok videos instantly! Required APIs 🔗 Content & Voiceover:** OpenAI (Paid), ElevenLabs (Free) Media Processing:** Cloudinary (Free), Replicate (Paid) Video Assembly:** 0codekit (Free), Creatomate (Free) Optional Integrations 🔗 Messaging & Sharing:** WhatsApp, Telegram, Gmail, Outlook Direct Upload:** TikTok Customization 🎨 Adjust script styles & voiceover preferences. Modify visuals to align with your brand. Optimize video length and format. 🚀 Start automating your TikTok content today and grow your audience on autopilot!

This workflow is a complete, production-ready solution for recovering abandoned carts in Shopify stores using a multi-channel, multi-touch approach. It automates personalized follow-ups via Email, SMS, and WhatsApp, tracks every customer interaction for multi-touch attribution, and enables advanced retargeting and analytics. Key features: Multi-step, timed recovery sequence (Email → SMS → Email → WhatsApp) Customer segmentation (new, returning, VIP) and A/B testing Dynamic discounting and personalized messaging Touchpoint logging to Google Sheets for attribution analysis Facebook Custom Audience retargeting for unrecovered carts Slack notifications for high-value cart recoveries What does this workflow do? Listens for abandoned cart events from Shopify (or any e-commerce platform) via webhook. Normalizes and enriches cart data by fetching full cart details and customer purchase history. Predicts the likely reason for abandonment (e.g., price sensitivity, checkout complexity, technical issues) using rule-based logic. Segments the customer (new, returning, VIP), assigns an A/B test group, and generates a personalized discount and checkout URL. Runs a timed, multi-channel recovery sequence: 1 hour after abandonment: Checks if the order is completed. If not, sends a personalized Email #1 and logs the touchpoint. 4 hours after abandonment: Checks again. If not recovered, sends an SMS with a discount code and logs the touchpoint. 24 hours after abandonment: Checks again. If not recovered, sends Email #2 (with social proof/urgency) and logs the touchpoint. 48 hours after abandonment: Final check. If not recovered, sends a WhatsApp reminder and logs the touchpoint. If the cart is still not recovered: Hashes customer identifiers and adds them to a Facebook Custom Audience for retargeting. Logs every touchpoint (email, SMS, WhatsApp) to a Google Sheet for multi-touch attribution analysis. Sends a Slack notification if a high-value cart is recovered. Why is this workflow useful? Boosts recovery rates:** By using multiple channels and personalized timing, you maximize the chance of recovering lost sales. Improves attribution:** Every customer interaction is logged, so you can analyze which channels and messages drive conversions. Enables advanced retargeting:** Unrecovered carts are automatically added to a Facebook Custom Audience for paid retargeting. Saves time:** Fully automated, with easy configuration for your store, messaging, and analytics. Scalable and extensible:** Easily adapt the sequence, add more channels, or integrate with other tools. How to install and configure Prerequisites n8n instance (v2.0.2+ recommended) Shopify store with API access Accounts and API credentials for: SendGrid (email) Twilio (SMS) WhatsApp Business API Google Sheets (service account) Facebook Graph API (for Custom Audiences) Slack (for notifications) Setup steps Import the workflow into your n8n instance. Configure the “Workflow Configuration” node: Set your Shopify domain, API URLs, Google Sheets ID, and high-value threshold. Connect all required credentials in the respective nodes: Shopify, SendGrid, Twilio, WhatsApp, Google Sheets, Facebook Graph API, Slack. Create a Google Sheet named “Touchpoints” with columns: cart_id, customer_id, touchpoint_type, timestamp, channel, ab_group. Set up the webhook in your Shopify store (or e-commerce platform) to trigger the workflow on cart abandonment. Test the workflow with a sample abandoned cart event to ensure emails, SMS, WhatsApp, and logging work as expected. Enable the workflow in n8n for live operation. Node-by-node breakdown Abandoned Cart Webhook:** Receives abandoned cart events. Workflow Configuration:** Stores global settings (API URLs, Shopify domain, Google Sheets ID, high-value threshold). Normalize Cart Data:** Cleans and standardizes incoming cart data. Fetch Cart Details / Fetch Customer History:** Enriches data with full cart and customer info. Predict Abandonment Reason:** Uses business logic to guess why the cart was abandoned. Personalization Engine:** Segments the customer, assigns A/B group, calculates discount, and builds checkout URL. Customer Segment Check / Device Type Check:** Applies routing logic for personalized messaging. Wait / Check Order Status / Generate & Send Messages:** Timed sequence for Email, SMS, and WhatsApp, with order status checks at each step. Log Touchpoint (Google Sheets):** Records every message sent for attribution. Attribution Merge:** Combines all touchpoints into a single journey for analysis. Hash Customer Data for Facebook / Add to Retargeting Audience:** Adds unrecovered carts to a Facebook Custom Audience. Check Cart Value Threshold / Notify High-Value Recovery:** Sends Slack alerts for high-value recoveries. Customization tips Adjust wait times and message content to fit your brand and audience. Add or remove channels (e.g., push notifications, phone calls) as needed. Expand the Google Sheet for deeper analytics (e.g., add UTM parameters, campaign IDs). Integrate with your CRM or analytics platform for end-to-end tracking. Troubleshooting Make sure all API credentials are set and tested. Check Google Sheets permissions for the service account. Test each channel (email, SMS, WhatsApp) individually before going live. Review the workflow execution logs in n8n for errors or failed steps.

WhatsApp Dietitian AI Chatbot Workflow Transform your WhatsApp into a professional nutrition consultant with this comprehensive AI-powered dietitian assistant. Built using n8n automation and Google Gemini AI, this workflow provides instant, intelligent nutrition advice to your clients 24/7. 🍽️ What It Does Meal Analysis: Users can send photos of their meals with captions like "analyze this meal" and receive detailed nutritional breakdowns including calories, macronutrients, and personalized recommendations. Nutrition Guidance: Answers questions about general nutrition, dietary restrictions, meal planning, and healthy eating habits with evidence-based information. Meal Recommendations: Suggests customized meals based on specific criteria like calorie targets, dietary preferences (vegan, keto, etc.), or available ingredients. 🚀 Key Features Dual Input Processing**: Handles both text questions and image analysis seamlessly Professional AI Responses**: Uses Google Gemini 2.0 Flash for accurate, contextual nutrition advice WhatsApp Optimized**: Responses formatted specifically for mobile messaging with emojis and clear structure Smart Routing**: Automatically detects message type (text vs image) and processes accordingly Structured Output**: Consistent, professional formatting for all responses Scope Management**: Stays within nutrition expertise and includes appropriate medical disclaimers 🛠️ Technical Stack Platform**: n8n workflow automation AI Model**: Google Gemini 2.0 Flash Integration**: WhatsApp Business API Message Types**: Text messages, images with captions Output**: Structured, conversational responses 📱 Perfect For Nutritionists and dietitians offering remote consultations Health coaches providing 24/7 client support Fitness professionals adding nutrition guidance Wellness businesses expanding their service offerings Anyone wanting to monetize nutrition expertise 🎯 Ready to Deploy This workflow comes with comprehensive documentation, clear setup instructions, and professional prompt engineering. Simply configure your WhatsApp Business API and Google Gemini credentials to start serving clients immediately. Transform your nutrition expertise into an automated, scalable WhatsApp service that works around the clock!

How It Works Top Branch Workflow A* The Market Intelligence: Patrols the Market:** Runs hourly to scrape competitor rates for future days. Gathers Intel:** If prices spike, it instantly checks event announcements to see if a major event is driving demand. Crunches Numbers:** Calculates the exact price gap and filters out noise. The Revenue Manager: Sets Strategy:** The AI Agent reviews the price gaps, competitor moves, and event signals. Reports:** Writes a strategic Executive Summary and sends it to your WhatsApp. Bottom Branch Workflow B* The Consultant: Recall: When you ask a question via WhatsApp, the bot retrieves the saved analysis, historical rates, and event schedule. Answer: It acts as an on-demand analyst, conducting further analysis to give an informed answer to questions Setup Steps Config: Add your hotel + competitor hotels (IDs/names) in the Config node. Monitor Window: Set how far ahead you want to monitor (e.g., daysAhead = 30) in the Config node. Sensitivity: Set how sensitive alerts should be (e.g., alert only if competitor moves > 10%) in the Significant Competitor Change node. Connect Credentials: Amadeus (to fetch hotel prices) WhatsApp (to send alerts) Postgres/SQL (to store price snapshots, history, summary) OpenAI (for the AI Agents) Event Source: Update the Fetch VCC nodes to scrape your local convention center or event site. Run a test: Trigger Workflow A manually and confirm you receive a WhatsApp alert. Reply to that WhatsApp message to test Workflow B (Q&A). Use Cases & Benefits For Revenue Managers: Automate the "rate shop" routine and catch competitor moves without opening a spreadsheet. For Sales & Marketing Teams: Go beyond raw data. Pairing "what changed" with "why changed" instantly. For Hotel Leadership: Perfect for GMs and division leaders who need instant, decision-ready alerts via WhatsApp. ⚡ Zero-Touch Efficiency: Eliminates hours of manual searching by automating rate checks 3x daily. 🧠 Contextual Intelligence: Tracks price AND explains why it moved by cross-referencing local events. 🤖 Actionable Strategy: AI doesn't just report numbers; it recommends specific pricing tactics. 📉 Long-Term Vision: Builds a permanent database of rate history, enabling the AI to answer complex trend questions over time. 📬 Want to Customize This? [email protected]

Description CashMate – Your AI-Powered WhatsApp Finance Agent Turn WhatsApp into a smart finance assistant that auto-registers you, logs transactions in natural language, extracts data from receipts and voice notes, and delivers instant report summaries—no apps, no charts, just lightning-fast insights in chat. Who is this for? Personal finance enthusiasts wanting effortless expense tracking Freelancers & solopreneurs juggling multiple incomes and expenses Small business owners needing quick bookkeeping on the go Busy professionals who prefer messaging over apps Privacy-minded users who host data on their own PostgreSQL What problem does this solve? Zero onboarding friction: Just send "Hi"—no forms, no sign-ups No app switching: Track everything right inside WhatsApp Manual entry eliminated: Natural-language, image, and voice input all auto-parsed Instant summaries: On-demand report requests—no dashboards to navigate How it works Auto-Registration New users: "Hi" → Creates your profile in PostgreSQL Returning users: Bypasses creation if your number already exists Intent Classification routes every message into one of five branches: Reports & Summaries Triggers on keywords like "today's report," "show May vs June," or "summary." Returns concise text summary of income, expenses, and net balance. Natural-Language Transactions Messages like "Give 200 to Mukesh for car repair" → AI extracts date, category, amount, payee → logs it. Receipt OCR Attach a receipt image → Gemini OCR node reads line-items → AI categorizes and logs. Voice-Driven Logging Send a voice note → Deepgram node transcribes → AI logs transaction. General Chat & Greetings "Hi," "Hello," or casual finance questions → Routed to chat branch for greetings or tips. Setup Prerequisites n8n instance (self-hosted or n8n.cloud, v1.0+) WhatsApp Business Cloud API credentials PostgreSQL database (host, port, user, password) OpenRouter/OpenAI API key for NLP Gemini API key for OCR Deepgram API key for voice transcription Quick Start Import CashMate.n8n.json into n8n. Rename nodes to suit your environment. Configure Credentials in n8n's Credentials section—avoid hard-coding keys. Activate workflow and message "Hi" from WhatsApp. Test by sending a sample expense text, image receipt, or voice note. > Note: All detailed setup instructions and deep configuration steps are provided in the sticky notes within the template. How to Customize Categories & Currencies:** Edit parsing logic in the Function nodes. AI Models:** Swap OpenAI/OpenRouter for GPT-4, Claude, or self-hosted alternatives. Multi-User Support:** Extend registration logic to tag team or family accounts. Additional Features:** Add budget alerts, multi-currency support, or bank integrations via Plaid. Example Interactions Text Transaction User: 300 given to James for the coffee CashMate: ✅ Transaction Added: • Date: 2025-06-24 • Category: Coffee & Beverages • Type: Expense • Amount: ₹300.00 • Counterparty: James Receipt Image (OCR) User: [sends image of café bill totaling ₹450] CashMate: ✅ Transaction Added: • Date: 2025-06-24 • Category: Coffee & Beverages • Type: Expense • Amount: ₹450.00 • Counterparty: Café Aroma Voice Transaction User: [voice note: "Paid 650 rupees for office stationery"] CashMate: ✅ Transaction Added: • Date: 2025-06-24 • Category: Office Supplies • Type: Expense • Amount: ₹650.00 • Counterparty: (none) `

This workflow listens for incoming WhatsApp messages that contain media (e.g., images) and automatically downloads the media file using WhatsApp's private media URL. The trigger node activates when a WhatsApp message with media is received. The media ID is extracted from the message payload. A private media URL is retrieved using the media ID. The media file is downloaded using an authenticated HTTP request. Ideal for: Archiving WhatsApp media to external systems. Triggering further automations based on received media. Integrating with cloud storage like Google Drive, Dropbox, or Amazon S3. Set up steps Connect your WhatsApp Business API account. Add HTTP credentials for downloading media via private URL. Set up the webhook in your WhatsApp Business account. Extend the workflow as needed for your use case (e.g., file storage, alerts).

This workflow enables seamless, bidirectional communication between WhatsApp and Slack using n8n. It automates the reception, processing, and forwarding of messages (text, media, and documents) between users on WhatsApp and private Slack channels. Key Features & Flow: WhatsApp to Slack Flow Trigger: The workflow starts with a WhatsApp Trigger node that listens for new incoming messages via a webhook. Channel Handling: It checks if a Slack channel with the WhatsApp sender’s number exists If not, it creates a private Slack channel with the sender's number as the name. Message Type Routing: A Switch Node (Message Type) inspects the message type (text, image, audio, document). Based on type: Text: Sends the message directly to Slack. Image/Audio/Document: Retrieves media URL via WhatsApp API → downloads the media → uploads it to the appropriate Slack channel. Slack to WhatsApp Flow Trigger: A Slack Trigger listens for new messages or file uploads in Slack. Message Type Routing: A second Switch Node (Checking Message Type) checks if the message is text or media. Routing Logic: Text Message: Extracts and forwards it to the WhatsApp contact (identified by the Slack channel name). Media/File Message: Retrieves media file URL from Slack → downloads it → sends it as a document via WhatsApp API. Key Integrations: WhatsApp Cloud API: For receiving messages, downloading media, and sending messages. Slack API: For creating/getting channels, posting messages, and uploading files. HTTP Request Node: Used to securely download media from Slack and WhatsApp servers with proper authentication. Automation Use Case: This workflow is ideal for businesses that handle customer support or conversations over WhatsApp and wish to log, respond, and collaborate using Slack as their internal communication tool.

⚡ Next-Gen Customer Support: Two-Way WhatsApp + Telegram Integration for 10k+ Clients Who is this workflow for This workflow is designed for **customer support teams, e-commerce founders, and operations managers** who want to handle thousands of customer queries seamlessly. Instead of building a brand-new chat application, it leverages WhatsApp (where customers already are) and Telegram (where your support team operates) to create a scalable, topic-based support system. If you are a brand handling 1000s of daily WhatsApp customer messages and need a structured way to map each customer into a dedicated support thread without chaos, this workflow is for you. What it does / How it works This two-way n8n automation bridges WhatsApp and Telegram by creating one Telegram forum topic per customer and syncing messages both ways: Incoming WhatsApp → Telegram When a new WhatsApp message arrives, the workflow checks if the customer already has a topic in Telegram. If yes → The message is forwarded into that existing topic. If no → A new topic is created automatically, the mapping is saved in the database, and the message is posted there. Result: every customer has a dedicated thread in your Telegram supergroup. Outgoing Telegram → WhatsApp When a support agent replies in a Telegram topic, the workflow looks up the linked WhatsApp number. The reply is sent back to the customer on WhatsApp, preserving context. Result: two-way synced conversations without building a custom app. How to set it up Configure WhatsApp Cloud API Create a Meta Developer account and register a WhatsApp Business number. Generate an access token and phone number ID. Configure Telegram Bot Use BotFather to create a bot and enable it in a **Telegram Supergroup with Topics**. Get the chat_id and allow the bot to create/send messages in topics. Database (Supabase/Postgres) Create a table wa_tg_threads to map phone_e164 ↔ telegram_topic_id ↔ supergroup_id. n8n Workflows Workflow A: WhatsApp → Telegram Trigger: WhatsApp Webhook Steps: Lookup customer → If exists send to topic, else create topic → Save mapping → Forward message. Workflow B: Telegram → WhatsApp Trigger: Telegram Webhook Steps: Filter only topic replies → Lookup mapping → Send WhatsApp message. Testing Send a WhatsApp message → Check Telegram topic created. Reply in Telegram topic → Ensure customer receives WhatsApp reply. Requirements A free or paid n8n instance (self-hosted or cloud). WhatsApp Cloud API credentials** (phone number ID + access token). Telegram Bot token* with access to a Supergroup with Topics* enabled. A Postgres/Supabase database to store thread mappings. Basic familiarity with editing HTTP Request nodes in n8n. How to customize the workflow Brand personalization:** Pre-populate first message templates (thank you, order status, delivery updates). Routing rules:** Assign specific agents to certain topics by ID ranges. Integrations:** Extend to CRMs (HubSpot, Zoho) or support platforms (Freshdesk, Zendesk). Notifications:** Push high-priority WhatsApp queries into Slack/Teams for instant alerts. Archival:** Auto-close inactive topics after N days and mark customers as dormant. Why Telegram instead of building a new App The client's requirement was clear: **use an existing, reliable, and scalable chat platform** instead of building a new app from scratch. Telegram Supergroups with Topics** scale to 100,000+ members and millions of messages, making them ideal for managing 10k+ customer threads. Agents don't need to install or learn a new tool---they continue inside Telegram, which is fast, free, and mobile-friendly. Building a custom chat app would require authentication, push notifications, scaling infra, and UX---all solved instantly by Telegram. This decision **saves development cost, accelerates deployment, and provides proven scalability**. Why this improves support productivity Organized by customer:** Each WhatsApp number has its own Telegram topic. No missed messages:** Agents can quickly scroll topics without drowning in one endless chat. Two-way sync:** Replies flow back to WhatsApp seamlessly. Scales automatically:** Handle 10k+ conversations without losing track. Leverages existing tools:** WhatsApp (customers) + Telegram (agents). Result: **faster responses, better tracking, and zero need to reinvent chat software.**

🚀 AI-Powered WhatsApp Customer Support for Shopify Brands This n8n template builds a WhatsApp support copilot that answers **order status* and product availability* from Shopify using LLM "agents," then replies to the customer in WhatsApp or routes to human support. Use cases "Where is my order?" → live status + tracking link "What are your best-selling T-shirts?" → in-stock sizes & variants Greetings / small talk → welcome message Anything unclear → handoff to support channel Good to know WhatsApp Business conversations are billed by Meta/Twilio/Exotel; plan accordingly. Shopify Admin API has rate limits (leaky bucket) --- stagger requests. LLM usage incurs token costs; cap max tokens and enable caching where possible. Avoid sending PII to the model; only pass minimal order/product fields. How it works WhatsApp Trigger\ Receives an incoming message (e.g., "Where is my order?"). Get Customer from Shopify → Customer Details → Normalize Input\ Looks up the customer by phone, formats the query (lower-case, emoji & punctuation normalization). Switch (intent router)\ Classifies into welcome, orderStatusQuery, productQuery, or supportQuery. Welcome path\ Welcome message → polite greeting → (noop placeholder). Order status path (Orders Agent) Orders Agent (LLM + Memory) interprets the user request and extracts needed fields. Get Customer Orders (HTTP to Shopify) fetches the user's latest order(s). Structured Output Parser cleans the agent's output into a strict schema. Send Order Status (WhatsApp message) returns status, ETA, and tracking link. Products path (Products Agent) Products Agent (LLM + Memory) turns the ask into a product query. Get Products from Shopify (HTTP) pulls best sellers / inventory & sizes. Structured Output Parser formats name, price, sizes, stock. Send Products message (WhatsApp) sends a tidy, human-readable reply Support path Send a message to support posts the transcript/context to your agent/helpdesk channel and informs the user a human will respond How to use Replace the manual/WhatsApp trigger with your live WhatsApp number/webhook. Set env vars/credentials: Shopify domain + Admin API token, WhatsApp provider keys, LLM key (OpenAI/OpenRouter), and (optionally) your support channel webhook. Edit message templates for tone, add your brand name, and localize if needed. Test with samples: "Where is my order?", "Show best sellers", "Hi". Requirements WhatsApp Business API (Meta/Twilio/Exotel) Shopify store + Admin API access LLM provider (OpenAI/OpenRouter etc.) Slack webhook for human handoff Prerequisites Active WhatsApp Business Account connected via API provider (Meta, Twilio, or Exotel). Shopify Admin API credentials** (API key, secret, store domain). Slack OAuth app** or webhook for human support escalation. API key for your LLM provider (OpenAI, OpenRouter, etc.). Customising this workflow Add intents: returns/exchanges, COD confirmation, address changes. Enrich product replies with images, price ranges, and "Buy" deep links. Add multilingual support by detecting locale and templating responses. Log all interactions to a DB/Sheet for analytics and quality review. Guardrails: confidence thresholds → fallback to support; redact PII; retry on API errors.

Flexible News Curator - Multi-Sources, AI Analysis, Summaries, Translation, and Settable Channels 🎬 Overview The Flexible News Curator workflow can automate the collection, filtering, AI-driven analysis, and summarization of news from diverse sources of your interest. Using customizable search themes, RSS feeds, and (optional) video descriptions, it delivers concise, quality news summaries via configurable channels. This workflow is designed to help reduce information overload and keep you updated effortlessly. Click the image below to watch the video guide: ✨ Features Multi-Source News Aggregation**: Collect news from customizable RSS feeds, SerpAPI, and Video Channel Feeds (if enabled). AI-Powered News Selection \& Summarization**: Uses advanced AI agents (Mistral Cloud Chat Model by default) to select, analyze, and summarize top news. Quality Assurance Step**: Optional AI-powered filtering to improve news selection quality before analysis. Multi-Language Translation \& Tone Customization**: Translate summaries and customize tone for localized or tailored consumption. Multi-Channel Delivery**: Send outputs via Email, Telegram, WhatsApp, Webhook, or save to disk. Advanced Filtering**: Regex-based filtering on URLs, titles, and content to exclude unwanted articles. Sub-Workflow Architecture**: Modular handling of video transcripts, content retrieval, multi-theme searching, and more. Flexible Scheduling \& Trigger Options**: Supports schedule-based triggering, email (IMAP) triggers, and webhook-based activation. (Optional) Video Search**: Video content descriptions via Video Channel Feeds. 👤 Who is this for? This workflow benefits professionals, researchers, marketers, and anyone who needs to stay informed about specific news themes without wasting time on irrelevant information or reading too many news to select the most interesting ones. 💡 What problem does this solve? The workflow tackles the challenge of information overload by automatically filtering, summarizing, and delivering the essential news tailored to your interests and preferences. It integrates various data sources and channels for comprehensive yet efficient news consumption. Ideal use-cases include: Monitoring breakthroughs in research fields Receiving daily business opportunity updates (e.g., real estate) Lower the cognitive load required to follow your favorite news Translating news summaries to your chosen language 🔍 What this workflow does The workflow gathers news from RSS feeds, search engines, and social media, then: Filters duplicates and irrelevant content via custom regex filters and date ranges. Applies optional AI-powered Quality Assurance for headline evaluation. Selects top news articles with AI analysis focused on user-defined criteria and audience. Summarizes individual articles using AI summarization agents, ensuring structured, consistent outputs. Optionally translates and adjusts the tone of summaries. Distributes summaries through configured channels such as email, social media, messaging apps, or webhook calls. 🔄 Workflow Steps News Gathering Fetch news using RSS feeds, SerpAPI search, and optionally video channel feeds. Standardize output structures for seamless merging. Employ sub-workflows for video transcript retrieval and looping over custom RSS feed lists. Filtering Remove duplicates and news outside the specified date range. Exclude articles matching user-defined keywords via regex filters in URLs, titles, and content. Limit the number of news articles for AI analysis. News Selection Optionally invoke an AI Quality Assurance agent to pre-filter headlines. Aggregate news for AI analysis. Select and summarize top news articles with AI agents using customizable criteria. Parse AI responses into defined JSON structures to ensure consistent data. News Summarization Prepare individual article content. Summarize content with AI agents and validate structured output. Sender Preparation Combine general summaries with selected top news summaries. Format final summaries as text and HTML suitable for delivery. Optionally apply translation and tone adjustment. Sending Deliver summaries through selected channels (Email, Telegram, WhatsApp, Webhook). Optionally save the output to disk as JSON. 📌 Expected Input / Configuration The workflow is primarily configured via the Configure Workflow Args node or the Global Variables custom node, with these key parameters: | Parameter | Description | Type | | :-- | :-- | :-- | | search_themes | List of keywords/themes to search in SerpAPI | List of strings | | datetime_delta | Number of days back to include news from; e.g., 0 = today | Integer | | link_censor | Regex to exclude unwanted URLs | Regex string | | title_censor | Regex to exclude unwanted titles | Regex string | | content_censor | Regex to exclude unwanted content | Regex string | | use_qa | Flag to enable AI Quality Assurance for headline filtering | Boolean | | max_news_analysis | Max number of articles sent to News Analyzer | Integer | | qa_max_news | Number of headlines the QA Agent analyzes | Integer | | qa_max_top_news | Number of headlines selected by QA Agent | Integer | | qa_check_criteria | Criteria used by QA Agent to discard low-quality headlines | List of strings | | qa_select_criteria | Criteria used by QA Agent to rank/select the best headlines | List of strings | | news_focus | What the News Analyzer should focus on while selecting news | String | | news_target_audience | Target audience description for the News Analyzer | String | | news_criteria | Instructions for the News Analyzer to identify relevant news | List of strings | | language | Language for news summaries; triggers translation if not English | String | | translator_tone | Tone for translation (e.g., casual, professional) | String | | translator_notes | Additional instructions for the translator | String | | email_sender | Email address used for sending (via SMTP) | String | | email_recipients | Recipient email addresses (comma-separated) | String | | email_subject | Email subject line | String | | telegram_chat_id | Telegram chat ID for sending notifications | String | | phone_number | Phone number for WhatsApp messages | String | | rss_feeds | Custom list of RSS feeds (objects with link and needs_content_search properties) | JSON array of objects | | video_rss_feeds | Custom list of video RSS feeds | JSON array of objects | | enable_video_search | Enable/disable video search functionality | Boolean | | enabled_senders | List of enabled delivery channels (email, telegram, whatsapp, webhook, save-to-disk) | List of strings | Hint: To add or combine keywords in censors, use the pattern "keyword1|keyword2|keyword3". 📦 Expected Output Structured JSON containing a general news summary, top news with summaries, and metadata, suitable for your preferred channel delivery. 📌 Example An example that includes workflow parameters is provided in a note within the workflow. ⚙️ n8n Setup Used n8n version:** 1.100.1 n8n-nodes-serpapi:** 0.1.6 n8n-nodes-globals:** 1.1.0 LLM Model:** mistral-small-latest (API) IMAP:** imap.gmail.com (Port 993) Platform:** Podman 4.3.1 on Linux Date:** 2025-07-15 ⚡ Requirements to Use / Setup Self-hosted n8n instance. (This workflow contains community nodes that are only compatible with the self-hosted version of n8n.) Install necessary custom nodes: n8n-nodes-serpapi n8n-nodes-globals (or use Edit Field (Set) node instead) Configure all sub-workflows bundled within this template (see Sub-Workflows Guide). Provide valid credentials to nodes for SerpAPI, Telegram, WhatsApp, Mistral Cloud Chat API, and SMTP (for email). Custom RSS feed list must be set by you in the workflow args. You must either install the SerpAPI custom node or deactivate it. ⚠️ Notes, Assumptions \& Warnings The workflow timeout is set to 30 minutes by default; adjust depending on your setup and workload. Duplicate removal is applied, but occasional overlaps might still appear depending on feed sources. This workflow assumes familiarity with n8n, RSS feeds, API key management and regex expressions. Video search only works for configured video channels; remember to respect the rights of these channels. Using AI agents (Mistral or substitute LLMs) requires access to their API services and keys. Out-of-the-box customization is done via the Global Variables node or direct workflow argument edits. ℹ️ About Us This workflow was developed by the Hybroht team of AI enthusiasts and developers dedicated to enhancing the capabilities of AI through collaborative processes. Our goal is to create tools that harness the possibilities of AI technology and more. For questions, support, or feature requests, reach out via [email protected]. ❓ Questions & Issues We will answer any questions, provided they are related to this workflow. Please contact us if there is any bug/issue with this workflow. We will assist you. ⚖️ Warranty & Legal Notice You can view the full license terms here. Please review them before making your purchase. By purchasing this product, you agree to these terms.

🤖Multi-Agent AI WhatsApp Bot for Service Businesses Transform your salon/service business with this streamlined WhatsApp automation system featuring Claude integration, zero-setup database management, and intelligent conversation handling. How it works Claude MCP Integration** - Direct connection to Claude Sonnet 4 via Model Context Protocol Streamlined 2-Agent System** - Booking Agent and Admin Agent (simplified from 5 for better reliability) GPT-5 Mini Primary** with Gemini 2.5 Flash backup for cost-effective processing Multi-Media Support** - Handles text, voice (Whisper transcription), images, and PDFs with cost extraction Smart Acknowledgments** - "One moment...", "Let me check availability..." during processing Rate Limiting & Spam Protection** - Configurable limits (default: 100 msg/hour) with professional UX Zero-Setup Database Management Autonomous Airtable Creation** - Bot creates all necessary tables automatically Complete CRUD Operations** - Create, edit, delete services and settings via WhatsApp Dynamic Business Configuration** - Modify hours, pricing, services conversationally Friend Booking Support** - "Book for my friend Sarah" functionality Set up steps WhatsApp Business API** setup (detailed instructions included) Airtable Base ID** extraction (store in Redis or hardcode - recommended) Google Calendar** integration for scheduling Redis** for caching, rate limiting, and conversation memory MCP Server** deployment for Claude integration Whatsapp** for notifications Key Features Booking Limit Control** - Default 6 appointments per customer (configurable in workflow) Service Name Matching** - GPT-5 Nano workflow for cost-optimized service recognition 24-Hour Advance Reminders** - Automatic WhatsApp reminders sent at 8 PM Conversation Memory** maintains context across interactions Error Resilience** with backup models and graceful failure handling Perfect for salons, spas, clinics, consulting services, or any appointment-based business. Complete business setup happens through conversational commands - no manual database configuration required.

Automated LinkedIn Job Monitoring with AI Filtering, Google Sheets & Telegram Alerts 📋 Description Automates LinkedIn job searches across multiple countries and categories, filters results with AI, stores data in Google Sheets, and sends weekly Telegram notifications. Perfect for professionals seeking opportunities in software development, web development, and digital marketing. Workflow Process: Weekly scheduler triggers SerpAPI searches → AI processes and filters jobs → Saves to Google Sheets → Sends country-by-country analytics via Telegram/WhatsApp. 🛠️ Prerequisites SerpAPI Account** (free 100 searches/month) - Get API key from serpapi.com Telegram Bot Token** - Create via @BotFather Google Sheets** - OAuth2 credentials + shareable spreadsheet WhatsApp Business Cloud** (optional) 📋 Setup Instructions Create Google Spreadsheet Set column headers: job_title | company_name | location | salary_raw | salary_numeric | remote_status | description | application_url | date_posted | country | timestamp_added | job_id | source Replace Placeholders YOUR_SERPAPI_KEY_HERE → Your SerpAPI key YOUR_GOOGLE_SHEET_ID_HERE → Spreadsheet ID from URL YOUR_TELEGRAM_CHAT_ID_HERE → Your Telegram chat ID YOUR_PHONE_NUMBER_HERE → WhatsApp number (optional) Configure Search Parameters Modify "Initialize Variables" node: job_types: "software development,web development,digital marketing" countries: "qatar,uae,saudi arabia" Set Credentials Add SerpAPI HTTP credentials Configure Telegram bot credentials Set up Google OAuth2 credentials Column Requirements: Ensure Google Sheets has exact column names as specified above for proper data mapping.

Multi-Platform AI Sales Agent with RAG, CRM Logging & Appointment Booking This workflow acts as a 24/7 sales agent, engaging leads across WhatsApp, Instagram, Facebook, Telegram, and your website. It intelligently transcribes audio messages, answers questions using a knowledge base, and uses modular sub-workflows to manage your CRM in Airtable and book appointments in Google Calendar. Who Is It For? This solution is designed for service-based businesses that require a sophisticated, multi-channel lead management and appointment booking system. Agencies, consultants, and clinics** looking to automate lead qualification and booking across text and voice messages. Sales teams** needing a robust system that separates CRM and calendar logic for easier management and scalability. Advanced n8n users** who want a powerful, agent-based framework that can be easily customized and extended. Key Features & Workflow This system is composed of a parent workflow that orchestrates the conversation and calls specialized sub-workflows (agents) to perform specific tasks. Omni-Channel Engagement:* Greets and converses with leads naturally on Website Chat, WhatsApp, Instagram, Facebook, and Telegram*. Voice Message Transcription:* Automatically transcribes incoming audio/voice notes from WhatsApp and Telegram* into text, allowing the AI to understand and respond without manual intervention. RAG-Powered Intelligence:* The AI agent draws answers from your dedicated PostgreSQL Knowledge Base (RAG)*, providing accurate information about your services, pricing, and process. A built-in tool allows you to load new knowledge documents from Google Drive. Modular CRM Agent (Sub-Workflow):* When the conversation requires CRM actions (like creating a contact or updating an opportunity), the main agent calls a dedicated Airtable CRM sub-workflow* to handle the task. Modular Calendar Agent (Sub-Workflow):* To book appointments, the main agent calls a separate Google Calendar sub-workflow*, which manages event creation, updates, and deletions. What You'll Need This workflow framework requires credentials for the following services: An AI provider (OpenAI is used for the main agent, transcription, and embeddings). PostgreSQL** database with the pgvector extension (for RAG and chat memory). Airtable** account (for the CRM sub-workflow). Google Calendar** account (for the Calendar sub-workflow). Telegram Bot** credentials. A Meta Developer Account (for WhatsApp, Instagram & Facebook). (Optional) Google Drive for loading knowledge documents. (Optional) Google Gemini for embeddings. How to Set It Up This is a modular system. You must set up the sub-workflows first. Deploy Sub-Workflows: Create two new, separate workflows using the provided templates for the CRM Agent and the Calendar Agent. Configure the credentials (Airtable, Google Calendar) within those workflows, then save and activate them. Link Sub-Workflows in Main Workflow: Return to this main workflow. In the "CRM Agent" and "Consultation Agent" tool nodes, select the new workflows you just created from the dropdown list. Configure Main Credentials: Securely add the remaining credentials (OpenAI, PostgreSQL, Telegram, and your Meta App) in this main workflow. Personalize the AI Agent: In the "Update Agent Details" node, fill in your business name, the agent's persona name, and your key services to customize the AI's personality. Load Your Knowledge (Optional): To populate the RAG database, use the manual trigger path starting with "When clicking ‘Execute workflow’" to download a document from Google Drive and insert it into your PostgreSQL vector store. Activate: Configure your channel-specific details (e.g., Phone Number ID in WhatsApp nodes), save the workflow, and activate it. Demo CRM Table: View on Airtable

This n8n template builds a meeting assistant that compiles timely reminders of upcoming meetings filled with email history and recent LinkedIn activity of other people on the invite. This is then discreetly sent via WhatsApp ensuring the user is always prepared, informed and ready to impress! How it works A scheduled trigger fires hourly to check for upcoming personal meetings. When found, the invite is analysed by an AI agent to pull email and LinkedIn details of the other invitees. 2 subworkflows are then triggered for each invitee to (1) search for last email correspondence with them and (2) scrape their LinkedIn profile + recent activity for social updates. Using both available sources, another AI agent is used to summarise this information and generate a short meeting prep message for the user. The notification is finally sent to the user's WhatsApp, allowing them ample time to review. How to use There are a lot of moving parts in this template so in it's current form, it's best to use this for personal rather than team calendars. The LinkedIn scraping method used in this workflow requires you to paste in your LinkedIn cookies from your browser which essentially let's n8n impersonate you. You can retrieve this from dev console or ask someone technical for help! Note: It may be wise to switch to other LinkedIn scraping approaches which do not impersonate your own account for production. Requirements OpenAI for LLM Gmail for Email Google Calendar for upcoming events WhatsApp Business account for notifications Customising this workflow Try adding information sources which are relevant to you and your invitees. Such as company search, other social media sites etc. Create an on-demand version which doesn't rely on the scheduled trigger. Sometimes you want to know prepare for meetings hours or days in advance where this could help immensely.

How it works An AI-powered sales agent on WhatsApp that handles product inquiries using your Supabase knowledge base and n8n catalog. Customers can send text, voice notes, or images to ask about products, pricing, and specs. The agent responds with detailed answers, product images, and FAQs, creating a complete self-service sales experience. (I primarily designed this for furniture business, consider tailoring it) Setup steps Connect Supabase credentials for your knowledge base and FAQs Configure n8n tables with your product catalog (prices, descriptions, image links) Set up WhatsApp Business API integration Add your product categories and common queries to the AI context Test with sample product questions and image uploads Customization tips Structure your catalog tables with clear columns (SKU, price, description, image_url) Add industry-specific terminology to the AI prompt Create templated responses for common FAQs to ensure consistency Enable voice-to-text transcription for better voice note handling Add product recommendation logic based on customer queries Set up image recognition for customers sending product photos to identify items

This n8n workflow automates scheduled checks for your target keywords’ positions in Google’s organic search results using SerpAPI. It logs new positions in Google Sheets, compares them to previous rankings, and sends notifications via WhatsApp and/or email based on the movement. Problem Statement & Target Audience Who is this for? This workflow is ideal for: SEO specialists monitoring keyword rankings. Website owners tracking performance. Agencies managing multiple client campaigns. It helps reduce manual effort by automatically checking rankings on a schedule and sending notifications only when there’s movement in position. Pre-conditions & API Requirements APIs & Services Used SerpAPI – Fetch Google search results Get API Key: https://serpapi.com/manage-api-key Docs for usage: SerpAPI Search API Note: Use Generic credential type in n8n for this to work with the preset configuration. Google Sheets API – To store and update keyword data Email API – To notify users of position changes WhatsApp API (e.g., Twilio, Ultramsg) – To send notifications > Setup help for Google Sheets, Email, and WhatsApp is available via the Docs tab in each respective node in n8n. Step-by-Step Workflow Explanation 🗓 1. Scheduled Trigger (Support Workflow) Marks all rows in the sheet as "notchecked" in the checkstatus column. This is the user-defined frequency trigger (e.g. weekly, daily). Triggers the main workflow. 🚀 2. Main Workflow Trigger Starts when a row with checkstatus = notchecked is found. 🔍 3. HTTP Node (SerpAPI Call) Sends a request to SerpAPI for each keyword. Fetches the current Google SERP for that keyword. 🧠 4. JavaScript Node (Parse Position) Loops through the SERP results and finds the position of the target URL. Extracts and returns the current rank. ✍️ 5. Google Sheets Node (Update Data) Writes the new ranking into the spreadsheet. Updates the currentposition and sets checkstatus to "checked". 🔀 6. Switch Node (Compare Rankings) Compares previousposition with currentposition: If rank has improved → send positive alert. If rank has dropped → send negative alert. If unchanged → no alert. 📩 7. Notification Nodes (WhatsApp / Email) Sends a message to chosen channels when a change is detected. Customization Guide ⏱️ Change Frequency Adjust the supporting schedule workflow to change how often the tracker runs. ✉️ Edit Notification Content Customize the WhatsApp and Email message content in their respective nodes. 🔗 Track Multiple URLs per Keyword (Advanced) Extend the JavaScript logic if you need to monitor several pages for the same keyword. 🌐 Expand Search Engine Targets SerpAPI also supports other search engines like Bing and Yahoo. Modify the request params to switch. How to Set Up This Workflow ✅ Step 1: Use This Google Sheets Template To get started quickly, make a copy of the template below: 👉 Google Sheets Template This template includes the required structure: keyword Website_url position timestamp checkstatus > ⚠️ Be sure to make your own copy to edit and connect via the Google Sheets node. 🔐 Step 2: Configure Your APIs SerpAPI:** Get API key from serpapi.com/manage-api-key Set credential type to Generic in n8n for compatibility. Google Sheets, Email & WhatsApp:* Use the instructions found in each node’s Docs tab* to connect your accounts. 📦 Step 3: Import the Workflow Both the main keyword tracking workflow and the supporting scheduler workflow are in one file ▶️ Step 4: The workflow will start Since the check status columns will be 'notChecked' schedule workflow. The update sheets node will update each processed row's checkstatus to 'checked' and the workflow will process the next row the schedule trigger workflow will update checkstatus = notchecked and triggers the keyword tracking automatically. 🎉 Done! From now on, your keyword positions will be monitored at the frequency you set. You’ll receive WhatsApp and/or email updates only when rankings change. in case you need customized workflows or wanna reach out here is my twitter and email.

Get notified when a customer completes a Stripe checkout — including all products they purchased in a single checkout session. Using the Stripe API can be tricky, especially when you're selling multiple products, order bumps, or recommended add-ons in one checkout. This workflow solves that for you. How it works The template listens for successful Stripe checkout events. When a payment is completed, it retrieves all items from the session, including main products, bumps, and extras — and sends a full breakdown straight to your chosen app. You can receive the notification on: Telegram** WhatsApp** Gmail** Or any other chat/notification service you prefer (Slack, Outlook etc. ) Who is this template for? Creators, marketers, and online sellers who: Use Stripe Checkout Want to track what customers are buying in real time Prefer to get notifications instantly instead of digging through Stripe logs How to set up Connect your Stripe account and choose where you want to receive notifications. Adjust the notification text for your preference, and you are done! Everything else is already configured in the template. Check out my other templates 👉 https://n8n.io/creators/solomon/

Template Guide for Employee Shortlisting AI Agent Automation Overview This template automates the process of shortlisting job applicants using ERPNext, n8n, and AI-powered decision-making tools like Google Gemini and OpenAI. It reduces manual effort, ensures fast evaluations, and provides justifiable decisions about applicants. This is ideal for businesses aiming to streamline their recruitment process while maintaining accuracy and professionalism. YouTube Tutorial:** For a full walkthrough of this template, visit: Integrate AI in ERPNext: Automate Recruitment Job Applicant Shortlisting in Seconds! What Does This Template Do? Webhook Integration with ERPNext: Automatically triggers the workflow when a job application is created in ERPNext. Resume Validation: Ensures resumes are attached and correctly processes various file formats like PDF and DOC. AI-Powered Evaluation: Uses AI to compare resumes against job descriptions and provides a: Fit Level (Strong, Moderate, or Weak) Score (0–100) Justification for the decision. Automated Decision Making: Based on AI-generated scores: Candidates with a score of 80 or higher are Accepted. Candidates below 80 are Rejected. Applications missing required fields or attachments are put On Hold. ERPNext Integration: Updates applicant records in ERPNext, including custom fields such as justification, fit level, and scores. Notifications: Notifies candidates via email, WhatsApp, or SMS about their application status. Step-by-Step Guide Step 1: Set Up ERPNext Webhook Go to Webhooks in ERPNext. Create a webhook for the Job Applicant DocType. Set the trigger to Insert. Pin and test the webhook to ensure proper data flow. Step 2: Import the Template into n8n Open your n8n instance. Import the provided workflow template. Check all nodes for proper configuration. Step 3: Configure Credentials Add your ERPNext API credentials to the ERPNext nodes. Add credentials for AI services like OpenAI or Google Gemini. Configure additional services like WhatsApp or email if you plan to use them for notifications. Step 4: Test Resume Validation Test how the workflow handles different file types (e.g., PDF, DOC, JPG). Ensure resumes without the proper format or attachment are flagged and rejected. Step 5: AI Evaluation The AI model (Google Gemini or OpenAI) will evaluate resumes against job descriptions. Customize the AI prompt to suit your job evaluation needs. The output will include a Fit Level, Score, Rating, and Justification. Step 6: Decision Automation The workflow automatically categorizes applicants: Accepted for scores ≥ 80. Rejected for scores < 80. On Hold if essential fields or attachments are missing. Step 7: Update ERPNext Records The workflow updates the Job Applicant record in ERPNext with: Status (Accepted, Rejected, On Hold) AI-generated Fit Level, Score, Rating, and Justification. Step 8: Notify Candidates Configure notification nodes (email, WhatsApp, or SMS). Inform candidates about their application status and include feedback if required. How It Works Trigger: The workflow starts when a job application is submitted in ERPNext. Validation: Checks if the resume is attached and in the correct format. AI Evaluation: Compares the resume with the job description and generates a decision. ERPNext Update: Updates the applicant's record with the decision and justification. Notification: Sends a personalized notification to the candidate. Dos and Don’ts Dos: Customize Prompts:** Tailor the AI prompt to match your specific job evaluation requirements. Test the Workflow:** Run sample data to ensure the process works as intended. Secure Your Credentials:** Keep your API credentials safe and do not share them publicly. Optimize for Different Formats:** Ensure the workflow can handle all types of resumes you expect. Don’ts: Avoid Manual Intervention:** Let the workflow handle most of the tasks to ensure efficiency. Do Not Skip Testing:** Always test the workflow with various scenarios to avoid errors. Do Not Overlook Notifications:** Ensure candidates are notified promptly to maintain professionalism. Customization Options Add logic for more file types (e.g., scanned images using OCR). Enhance the AI prompts to analyze more complex resume data. Integrate additional tools like Slack or Trello for recruitment tracking. Resources GET n8n Now N8N COURSE n8n Book YouTube Tutorial:** For a full walkthrough of this template, visit: SyncBricks YouTube Channel Detailed Guides and Courses:** Learn more about ERPNext and AI-driven automation at: SyncBricks LMS Support If you encounter issues or want to explore more possibilities with AI-driven automation, feel free to reach out: Email:** [email protected] Website:** ERPNext and Other Courses LinkedIn:** Amjid Ali Let me know if you'd like further details or modifications to the guide!

This workflow implements an AI-powered WhatsApp booking assistant for a hair salon. The system allows customers to book, reschedule, or cancel appointments automatically via text or voice messages on WhatsApp. The workflow supports both text and voice messages. An AI agent manages the conversation logic, determines the user's intent, and calls the appropriate tools to perform actions such as checking availability, creating appointments, rescheduling bookings, or canceling events. The system also includes guardrails to filter unsafe or irrelevant inputs and escalation mechanisms to notify the team when a request falls outside supported tasks. Key Advantages ✅ 24/7 Automated Appointment Booking Customers can book, reschedule, or cancel appointments at any time through WhatsApp without requiring manual staff intervention. ✅ Multi-Modal Communication (Text + Voice) The workflow supports both text messages and voice messages. Audio messages are automatically transcribed and processed by the AI assistant. ✅ Intelligent AI Assistant An AI agent manages the conversation, understands user intent, and automatically performs actions such as checking calendar availability or creating appointments. ✅ Real-Time Calendar Integration The assistant connects directly to Google Calendar to: check available time slots create new bookings update existing appointments cancel reservations This ensures real-time accuracy. ✅ Automatic Client Management Customer information such as phone number, name, and service type is stored and updated in Google Sheets, creating a lightweight CRM database. ✅ Conversation Memory The system stores chat history in PostgreSQL, allowing the AI assistant to maintain context during conversations and deliver a more natural experience. ✅ Smart Error Handling and Escalation If the AI cannot handle a request (for example, a question unrelated to appointments), the workflow automatically: notifies the team via email escalates the conversation for human assistance. ✅ Secure and Controlled AI Responses Guardrails are implemented to prevent irrelevant or unsafe responses, ensuring that the assistant follows defined policies and tasks. ✅ Omnichannel Architecture The workflow is designed to work with: WhatsApp messages chatbot interface (chat trigger) This allows the same logic to power multiple communication channels. ✅ Scalable Automation The system is fully automated and can handle multiple simultaneous conversations, reducing operational workload and improving customer service efficiency. How it works Input Handling (WhatsApp & Chat): It listens for incoming messages from either a WhatsApp Trigger or a Chat Trigger. WhatsApp: It processes both text messages and voice notes. If a voice note is received, it automatically downloads the audio, transcribes it using OpenAI (Whisper), and converts it into text for the AI to process. The user's phone number (for WhatsApp) or session ID (for Chat) is stored as a sessionId to maintain conversation context. Guardrails (Security & Policy): Before the message reaches the main AI agent, it passes through a Guardrails node (using Google Gemini). This acts as a safety filter to check for jailbreak attempts or inappropriate content, ensuring the conversation stays within company policies. AI Agent (The Virtual Assistant): The cleaned-up message is sent to the AI Agent ("Virtual Assistant"). The agent is prompted to act as "Emma" and follows strict instructions: Identify User: It first uses the New client tool to check a Google Sheet to see if the user is already registered. Manage Appointments: Based on the user's request (book, reschedule, cancel), it intelligently calls specific tools in the correct order. Date Logic: It is aware of the current date and time to calculate correct future dates (e.g., interpreting "this Thursday"). Tool Execution (Actions): The agent has access to several tools to perform actions: Google Sheets (New client, Add client): To check if a client exists and add new clients to a spreadsheet. Google Calendar (Get events, Create event, Update event, Delete event): To check availability and manage appointments. The Get events tool is configured to look for slots in the next 30 days. Gmail (Send Email): To notify the team if a user asks for something outside the scope (e.g., pricing, product questions). WhatsApp HITL / Chat HITL (Escalation): To hand over the conversation to a human agent for complex requests. Response Delivery: The AI agent's text response is routed back to the user. On WhatsApp: It intelligently handles the response format. If the original message was text, it sends a text reply. If the original message was a voice note, it uses OpenAI's TTS to convert the text reply into an audio message and sends that back. Setup steps To get this workflow running, you need to configure the following credentials and nodes: Configure Credentials: Google Calendar OAuth2: Connect your Google account (used in Calendar nodes). Google Sheets OAuth2: Connect your Google account to access the spreadsheet. Gmail OAuth2: Connect your Google account to send notification emails from [email protected]. WhatsApp API: Connect your WhatsApp Business API credentials (Phone Number ID). OpenAI API (OpenRouter): Provide your API key for audio transcription and text-to-speech. Google Gemini API: Provide your API keys for the main AI model (Google Gemini Chat Model) and the Guardrails model (Google Gemini Chat Model1). Postgres: Configure the connection to your Postgres database for chat memory. Configure Google Sheets: Create a Google Sheet. Update the Document ID in the New client and Add client nodes with your sheet's ID. Ensure the sheet has columns for Phone Number, Client, and Service. Configure Google Calendar: Verify that the calendar ID in the Calendar nodes is correct and accessible. Configure WhatsApp Triggers & Actions: The WhatsApp Trigger node needs to be connected to your WhatsApp Business App. The Send message and Send audio nodes must have the correct Phone Number ID for your WhatsApp Business number. Update Email Recipient: In the Send Email tool (for escalations), change the sendTo email address from [email protected] to the actual email of the team that should receive these notifications. Review AI Prompts: Open the "Virtual Assistant" (AI Agent) node and review the system message. Update the salon name ("Cuts & Styles"), stylist name ("Alex Carter"), and address to match your business. Check the "Guardrails" node to adjust the safety threshold if necessary. 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Build a WhatsApp AI shopping bot with virtual try-on using Gemini 📌 Overview This workflow fully automates your T-shirt store's WhatsApp shopping experience using GPT for intent detection, MongoDB Atlas for vector-based product search, Redis for session management, and Google Gemini for AI-powered virtual try-on. It automatically handles customer messages, finds relevant products, processes orders, and generates realistic try-on images — all inside WhatsApp, with no app or website required. Customers can search for T-shirts, place orders, and virtually try on items in a single conversation. Redis ensures fast product caching and session tracking. MongoDB Atlas stores the product catalog and orders. Google Sheets logs every order automatically. Gemini generates realistic try-on images from customer selfies. This workflow eliminates manual order handling, improves customer experience, and gives store owners full visibility into orders and product searches. ⚙️ How it works This workflow runs automatically when a customer sends a WhatsApp message. 🔍 Product search 💬 Receives the customer message via WhatsApp Business API 🧠 GPT classifies the intent as product search, recommendation, or general query ⚡ Checks Redis cache for existing results (TTL: 1 hour) 🔎 On a cache miss, runs MongoDB Atlas vector search using OpenAI embeddings 🛍️ Sends matching products as interactive WhatsApp cards with Order Now and Virtual Try-On buttons 🛒 Order flow 👆 Triggered when the customer taps the Order Now button 📦 AI agent fetches product details from MongoDB 🗃️ Creates a new order document in MongoDB 📊 Logs the order to Google Sheets automatically ✅ Sends an order confirmation message to the customer via WhatsApp 👗 Virtual try-on flow 👆 Triggered when the customer taps the Virtual Try-On button 💾 Stores the product ID in Redis (TTL: 10 minutes) 📸 Prompts the customer to send a clear front-facing selfie 🔍 Gemini validates that exactly one real person is in the photo 🖼️ Merges the product image and selfie and generates a realistic try-on image 📩 Sends the try-on result back to the customer via WhatsApp 🗑️ Clears the Redis context after delivery 🛠 Setup steps Import this workflow into n8n Connect your WhatsApp Business Cloud API credentials Connect your OpenAI API credentials (for embeddings and GPT model) Connect your Google Gemini API credentials Connect your MongoDB Atlas credentials and create a vector index named ShopingBot on the product collection Connect your Redis credentials Connect your Google Drive service account credentials Connect your Google Sheets service account credentials Import your product catalog with embeddings into the MongoDB product collection Activate the workflow The workflow will run automatically when customers send WhatsApp messages. 🚀 Features 🧠 AI-powered shopping 🤖 Automatically classifies customer intent using GPT 🔎 Semantic product search using OpenAI embeddings and MongoDB Atlas vector search ⚡ Redis caching for ultra-fast repeated search results (TTL: 1 hour) 💬 Interactive WhatsApp product cards with Order Now and Virtual Try-On buttons 🔄 Sliding window session memory (last 20 messages per user) 🛒 Order management 📦 Fully automated order creation saved to MongoDB 📊 Automatic order logging to Google Sheets 🤖 AI agent handles the complete order flow without manual input ✅ Instant order confirmation sent to the customer via WhatsApp 👗 Virtual try-on ✨ AI-powered try-on image generation using Google Gemini 📷 Selfie validation ensures exactly one real person is in the photo 🖼️ Product and selfie images resized and merged before generation 📩 Try-on result delivered directly in the WhatsApp conversation 🗑️ Redis TTL automatically clears try-on context after delivery 🔐 Security and reliability 🛡️ Advanced message validation with spam and XSS protection ❌ Unsupported message types rejected with friendly error messages 🔁 Retry logic on critical HTTP request nodes 📦 Modular workflow architecture for easy customisation and scaling 📋 Requirements You need the following accounts and credentials: 🔧 n8n 📱 WhatsApp Business Cloud API 🤖 OpenAI API (embeddings and GPT model) ✨ Google Gemini API 🍃 MongoDB Atlas (with vector index named ShoppingBot on the product collection) ⚡ Redis server 📁 Google Drive (service account) 📊 Google Sheets (service account) 🎯 Benefits 🚀 Fully automated WhatsApp shopping experience 🙌 No manual order handling required 👗 Customers can try on products before buying ⚡ Fast product search with Redis caching 📊 All orders automatically tracked in Google Sheets 💼 Reduces support workload for store owners 🕐 Works 24/7 without human intervention 👨‍💻 Author BytezTech Pvt Ltd

How it works This AI agent manages your Streak CRM via WhatsApp. Send messages to create contacts, add boxes to pipelines, update stages, link contacts to boxes, and retrieve information, add and get tasks all through natural conversation. Setup steps Connect your Streak API credentials (Basic Auth) Configure WhatsApp Business integration Add your Streak pipeline keys to the workflow Test with a simple command like "create contact John Doe" Customization tips Add custom Streak fields to the AI's tool descriptions Modify pipeline stages to match your workflow Adjust AI prompts to recognize your team's terminology Enable additional Streak operations (comments, tasks, files) The agent worked perfectly when you give it access to streak API documentation, to attain even more complex tasks

How it works Transform your WhatsApp messages into an organized journal with AI-powered transcription and media management. • Receive text, audio, or image messages via WhatsApp • Automatically transcribe audio messages using Google Gemini AI • Store media files in organized Google Drive folders • Update a central Google Doc with timestamped entries • Get instant confirmation messages Set up steps WhatsApp Business API: Set up credentials and configure the WhatsApp Trigger node Google Doc: Create a new Google Doc and paste its URL in all three "Actualizar documento" nodes (replace YOUR_GOOGLE_DOC_URL) Google Drive folders: • Create an "Audio" folder and paste its ID in the "Subir Audio" node (replace YOUR_AUDIO_FOLDER_ID) • Create an "Imagenes" folder and paste its ID in the "Subir Imagenes" node (replace YOUR_IMAGE_FOLDER_ID) Authorized numbers: Add your authorized WhatsApp phone numbers in the "If" node (replace YOURNUMBERPHONE(1), YOURNUMBERPHONE(2), YOURNUMBERPHONE(3) with numbers in international format without + sign, e.g., 5491112345678) WhatsApp Phone Number ID: Replace YOUR_WHATSAPP_PHONE_NUMBER_ID in all three confirmation nodes with your WhatsApp Business Phone Number ID Google Gemini: Configure your Google Gemini API credentials in the "Transcribir audio" node Requirements Credentials needed: • WhatsApp Business API account and credentials • Google Workspace account (Google Docs + Google Drive) • Google Gemini API key for audio transcription Nodes used: • WhatsApp Trigger • WhatsApp (for sending messages and downloading media) • Google Docs (for journal updates) • Google Drive (for media storage) • Google Gemini (for audio transcription) • If, Switch, HTTP Request nodes Perfect for content creators, researchers, writers, or anyone who wants to capture thoughts on-the-go via WhatsApp and have them automatically organized in a searchable, timestamped journal with AI-powered transcriptions!

How It Works This workflow automates tax compliance monitoring and revenue analysis for accounting teams and finance managers handling multi-source income data. It solves the critical problem of manually tracking revenue streams, identifying tax anomalies, and ensuring regulatory compliance across multiple data sources. The system fetches revenue data from accounting software via MagicCSV, processes it through three specialized AI models for categorization, anomaly detection, and compliance verification, then automatically syncs validated results to accounting systems and sends tax summary reports via email and WhatsApp. This eliminates hours of manual review, reduces compliance errors, and provides real-time tax insights. Setup Steps Configure MagicCSV integration with your accounting software API credentials Add Anthropic API key for categorization, anomaly detection, and compliance models Connect accounting software webhook/API for bidirectional sync Set up Gmail authentication for automated report distribution Configure WhatsApp Business API credentials for instant alerts Prerequisites Anthropic API access, MagicCSV account, accounting software with API capabilities Use Cases Multi-entity corporations tracking cross-border revenue, e-commerce businesses with diverse income streams Customization Modify AI prompts for industry-specific tax rules, add custom anomaly thresholds Benefits Reduces manual tax review time by 80%, minimizes compliance errors through triple AI validation

This automated n8n workflow transforms raw CSV data into qualified, enriched lead databases with verified emails and AI-generated personalization. It processes uploaded CSV files through multiple validation, enrichment, and sorting stages before delivering organized results via Google Drive, WhatsApp, or Google Sheets. How It Works Stage 1: Data Intake & Normalization Form Submission: User uploads a CSV/XLSX file and selects: Delivery method (Google Drive, WhatsApp, or Google Sheets with processing) Two personalization prompts for AI-generated messages Column Mapping: The workflow automatically recognizes and standardizes 100+ column name variations into consistent fields Deduplication: Removes duplicate entries by website URL and contact name Initial Filtering: Identifies and flags invalid websites (social media profiles, link shorteners) Stage 2: Data Quality Routing The workflow analyzes each record and routes it based on available data: Route A: Invalid Website → Sends directly to "x Website" sheet Route B: No Website → Verifies existing email and categorizes by validity Route C: Valid Website + Email → Proceeds to email verification and enrichment Route D: Valid Website - Email → Scrapes website to find email addresses. Stage 3: Email Discovery & Verification For records needing enrichment: Website Scraping: Fetches HTML content from company websites Email Extraction: Uses regex patterns to identify email addresses AI Selection: GPT-5-NANO chooses the most relevant email from multiple options Dual Verification: Primary check via Reoon API (deliverability, SMTP, safety) Backup verification if primary fails Personal Email Processing: Separately validates personal emails when present Stage 4: Website Intelligence Gathering Parallel to email processing: Extracts HTML title tags for company context Captures meta descriptions for business understanding Pulls H1 headings for content insight Handles scraping failures gracefully with empty placeholders Stage 5: Email Categorization Logic Records are sorted into buckets: +1 Email**: Has exactly one verified email (business OR personal OR newly found) +2 Email**: Has two or more verified emails Single Source Records**: Only business email OR only personal email Stage 6: AI Personalization For records with verified emails: Context Assembly: Combines name, company, job title, website metadata, industry, keywords AI Processing: Sends to GPT-5-NANO or Gemini with user's custom prompts Structured Output: Generates: Cleaned contact name Shortened company name Personalization message 1 (per user prompt) Personalization message 2 (per user prompt) Stage 7: Final Delivery Based on user's initial selection: Google Drive**: Uploads timestamped CSV, sends email with link WhatsApp**: Converts to XLSX and sends document Google Sheets**: Populates separate sheets by category with completion email How To Use Active n8n instance with required credentials: Google Drive API access Google Sheets API access Gmail API access (for notifications) WhatsApp Business API credentials Reoon Email Verifier API keys OpenAI API key (GPT-5-NANO) Optional: Google Gemini API key Setup Steps Configure Google Sheets Destinations Create or use existing Google Sheets for data categorization: +1 Email Sheet**: Update document ID in "+1 Email" node +2 Email Sheet**: Update document ID in "+2 Email" node x Website Sheet**: Update document ID in "x Website Data" node No Website Sheet**: Update document ID in "- Website +- Email +- Phone Number" node Ensure all sheets have matching column headers as defined in the workflow. Set Up Google Drive Folder Create a destination folder in Google Drive Update the folder ID in the "Upload file" node Ensure the service account has write permissions Configure WhatsApp Add your WhatsApp Business Phone Number ID in the "Send CSV" node Update the recipient phone number (format: +country code) Customize Email Notifications Update sender and recipient emails in "Send a message" and "Send a Success Message" nodes Modify email templates as needed Verify API Keys Check that all API credentials are active: Reoon Email Verifier keys (two instances for redundancy) OpenAI API key for GPT-5-NANO All Google API credentials

How It Works This workflow automates cross-platform content distribution from Instagram to YouTube with intelligent AI enhancement. Designed for content creators, social media managers, and digital marketers who need to maximize their content reach across platforms efficiently. The template solves the challenge of manual video repurposing by automating the entire process from content retrieval to optimized publishing. It retrieves Instagram videos on schedule, generates engaging metadata using dual AI models (Anthropic Claude for creative titles/descriptions), uploads to YouTube, logs performance metrics to Google Sheets, and sends WhatsApp notifications upon completion. The workflow intelligently routes tasks between AI providers: Claude's language capabilities create compelling and platform-optimized content. This dual-model approach delivers superior results compared to single-AI solutions, combining creativity with precision for maximum engagement. Setup Steps Configure Instagram credentials Add Anthropic API key for Claude model in AI nodes Connect YouTube account and configure upload settings Link Google Sheets with target spreadsheet ID for logging Add WhatsApp Business API credentials Prerequisites Instagram Business/Creator account with API access Use Cases Social media agencies managing multiple client accounts Customization Modify AI prompts for brand-specific tone, adjust scheduling frequency Benefits Saves 2-3 hours daily on manual uploads, ensures consistent posting schedules

Overview This workflow is designed to monitor the Top 5 cryptocurrencies in real-time, calculate trading signals (BUY, SELL, HOLD), and send human-readable alerts through multiple channels. It integrates data fetching, signal processing, AI-generated insights, and multi-channel notifications to provide a professional-grade crypto monitoring solution. Setup Schedule the trigger Fetch real-time coin data (CoinGecko, Binance API) Filter only required fields Check each data from loop Add the logic for minimum percentage comparison Use AI for analysis enhanced insights Send the notification only if signal is 'SELL' or 'BUY' Key Features Real-Time Crypto Monitoring: Continuously evaluates the top 5 cryptocurrencies for trading signals. Dynamic Signal Calculation: Generates BUY, SELL, HOLD signals based on 24h price change. If price changed below or above 2% the dynamic signal will assign to dedicated coin. Signal Change Alerts: Sends notifications only when meaningful changes occur. Human-Readable Messaging: Converts numeric signals into readable alerts. AI Insights: Provides explanations or trading advice via OpenAI. Multi-Channel Delivery: Supports WhatsApp, Telegram, and Email. Looped Processing: Each coin is processed independently for accurate alerting. Wait / Delay Node: Prevents API rate limit issues and controls alert flow. Requirements OpenAI API WhatsApp API Telegram API SMTP Credentials or Gmail Credentials.

How it works This workflow acts as an instant SDR that replies to new inbound leads across multiple channels in real time. It first captures and normalizes all incoming lead data into a unified structure. The workflow then evaluates IST working days and hours, generates a context-aware AI response, and routes the reply to the correct channel. Finally, it logs the full interaction, response status, and timing into Google Sheets. Step-by-step Step 1: Lead intake & normalization** Incomming Lead whatsapp1 – Receives new WhatsApp lead messages via webhook. Incomming Lead facebook1 – Captures incoming Facebook lead messages. Incomming Lead instagram1 – Listens for Instagram lead messages. Incomming Lead linkdin1 – Captures LinkedIn lead messages. Incomming Lead Website1 – Receives website form submissions. Normalize Lead Data6 – Normalizes WhatsApp lead fields. Normalize Lead Data7 – Normalizes Facebook lead fields. Normalize Lead Data8 – Normalizes Instagram lead fields. Normalize Lead Data9 – Normalizes LinkedIn lead fields. Normalize Lead Data5 – Normalizes website lead data. Switch2 – Merges all normalized leads into a single processing path. Step 2: Working hours & AI response** Extract Day and Hours1 – Converts timestamps to IST and extracts day and time. Is Working Day and Working Hour?1 – Determines whether the lead arrived during business hours. Code in JavaScript3 – Builds the AI prompt using lead details and timing context. Get Ai Response1 – Generates a short, human-like response. Step 3: Send reply & log data** Code in JavaScript4 – Combines AI output with normalized lead data. Switch3 – Routes the response based on the source channel. Send message – Sends WhatsApp replies. Send Instagram Message1 – Sends Instagram responses. Send Facebook Messages1 – Sends Facebook replies. Send Linkdin Messages1 – Sends LinkedIn responses. Send a message1 – Sends email replies for website leads. Code in JavaScript5 – Finalizes response status and metadata. google-sheet-name – Appends or updates lead and response data in Google Sheets. Why use this? Replies instantly to leads across all major inbound channels Keeps all lead data standardized and easy to manage Automatically respects IST working days and hours Reduces manual SDR workload without losing response quality Maintains a complete response log for reporting and follow-up

How it works This workflow monitors Meta Ads and Google Ads campaigns on a daily schedule to detect performance drops. It fetches yesterday’s campaign data, standardizes metrics, and calculates CTR and ROAS against fixed benchmarks. Campaigns that fall below thresholds are flagged automatically. Alerts are then sent across multiple channels and all results are logged in Google Sheets for tracking. Step-by-step Step 1: Fetch ad performance data** Schedule Trigger (Daily Ad Check2) – Runs the Meta Ads performance check at the scheduled time. HTTP Request (Fetch Meta Ads Data) – Retrieves campaign metrics from the Meta Ads API. Set (Set Benchmarks) – Normalizes Meta Ads data and assigns platform details. Schedule Trigger (Daily Ad Check3) – Runs the Google Ads performance check at a separate scheduled time. Google Ads (Get many campaigns) – Fetches campaign performance data from Google Ads. Set (Set Benchmarks4) – Normalizes Google Ads data and assigns platform details. Step 2: Detect performance drops** Code (Detect Performance Drop) – Calculates CTR and ROAS, compares them with predefined benchmarks, and flags drops. If – Filters only campaigns where a performance drop is detected. Split In Batches (Loop Over Items) – Processes each affected campaign individually. Step 3: Alert and log results** WhatsApp (Send message1) – Sends instant WhatsApp alerts for critical visibility. Slack (Send a message) – Posts detailed alerts to a Slack channel. Gmail (Send a message4) – Sends email notifications with full campaign metrics. Code (Code in JavaScript) – Recombines campaign data after notifications. Wait (Wait1) – Ensures alert delivery before logging. Google Sheets (your-google-sheets-name) – Appends or updates campaign records for reporting and audit history. Why use this? Catch CTR and ROAS drops before ad spend is wasted. Monitor Meta Ads and Google Ads in a single automated flow. Notify teams instantly via WhatsApp, Slack, and Email. Keep a centralized performance log for analysis and reporting. Reduce manual checks with consistent daily monitoring.

WhatsApp AI Sales Agent using PDF Vector Store This workflow turns your WhatsApp number into an intelligent AI-powered Sales Agent that answers product queries using real data extracted from a PDF brochure. It loads a product brochure via HTTP Request, converts it into embeddings using OpenAI, stores them in an in-memory vector store and allows the AI Agent to provide factual answers to users via WhatsApp. Non-text messages are filtered and only text queries are processed. This makes the workflow ideal for building a lightweight chatbot that understands your product documentation deeply. Quick Start: 5-Step Fast Implementation Insert your WhatsApp credentials in the WhatsApp Trigger and WhatsApp Send nodes. Add your OpenAI API Key to all OpenAI-powered nodes. Replace the PDF URL in the HTTP Request node with your own brochure. Run the Manual Trigger once to build the vector store. Activate the workflow and start chatting from WhatsApp. What It Does This workflow converts a product brochure (PDF) into a searchable knowledgebase using LangChain vector embeddings. Incoming WhatsApp messages are processed and if the message is text, the AI Sales Agent uses OpenAI + the vector store to produce accurate, brochure-based answers. The AI responds naturally to customer queries, supports conversation memory across the session and retrieves information directly from the brochure when needed. Non-text messages are filtered out to maintain clean conversational flow. The workflow is fully modular: you can replace the PDF, modify AI prompts, plug into CRM systems or extend it into a broader sales automation pipeline. Who’s It For This workflow is ideal for: Businesses wanting a WhatsApp-based AI customer assistant. Sales teams needing automated product query handling. Companies with large product catalog PDFs. Marketers wanting a zero-code product brochure chatbot. Technical teams experimenting with LangChain + OpenAI inside n8n. Requirements to Use This Workflow To run this workflow successfully, you need: An n8n instance (cloud or self-hosted). A WhatsApp Business API connection. An OpenAI API key. A publicly accessible PDF brochure URL. Basic familiarity with n8n node configuration. Optional: A custom vector store backend (Qdrant, Pinecone) – the template uses in-memory storage. How It Works & How To Set Up Import the Workflow JSON Upload the workflow JSON provided. Configure WhatsApp Trigger Open WhatsApp Trigger Add your WhatsApp credentials Set the webhook correctly to match your n8n endpoint Configure WhatsApp Response Nodes The workflow uses two WhatsApp send nodes: Reply To User** → Sends AI response Reply To User1** → Sends “unsupported message” reply Add your WhatsApp credentials to both. Replace the PDF Brochure In get Product Brochure (HTTP Request): Update the url parameter with your own PDF Run the PDF → Vector Store Setup (One-Time Only) Use the Manual Trigger ("When clicking ‘Test workflow’") to: Download the PDF Extract text Split into chunks Generate embeddings Store them in Product Catalogue vector store > You must run this once after importing the workflow. Set OpenAI Credentials Add your OpenAI API Key to the following nodes: OpenAI Chat Model OpenAI Chat Model1 Embeddings OpenAI Embeddings OpenAI1 Review the AI Agent Prompt Inside AI Sales Agent, you can edit the system message to match: Your brand Your product types Your tone of voice Activate the Workflow Once activated, WhatsApp users can chat with your AI Sales Agent. How to Customize Nodes? Here are common customization options: Customize the PDF / Knowledgebase Change the URL in get Product Brochure or Upload your own file via other nodes. Customize AI Behavior Edit the systemMessage inside AI Sales Agent: Change personality Set product rules Restrict/expand scope Change Supported Message Types Modify Handle Message Types switch logic to allow: Image → OCR Audio → Whisper Documents → Additional processing Modify WhatsApp Message Templates Inside the textBody of response nodes. Extend or replace Vector Store Swap vectorStoreInMemory with: Qdrant Pinecone Redis vector store By updating the vector store node. Add-Ons (Optional Enhancements) You can extend this workflow with: Multi-language support Add OpenAI translation nodes before agent input. CRM Integration Send user queries and chat logs into: HubSpot Salesforce Zoho CRM Product Recommendation Engine Use embeddings similarity to suggest products. Order Placement Workflow Connect to Stripe or Shopify APIs. Analytics Dashboard Log chats into Airtable / Postgres for analysis. Use Case Examples Here are some practical uses: Product Inquiry Chatbot Customers ask about specs, pricing, or compatibility. Digital Catalog Assistant Converts PDF brochures into interactive WhatsApp search. Sales Support Bot Reduces load on human sales reps by handling common questions. Internal Knowledge Bot Teams access manuals, training documents, or service guides. Event/Product Launch Assistant Provides instant details about newly launched items. And many more similar use cases where an AI-powered WhatsApp assistant is valuable. Troubleshooting Guide | Issue | Possible Cause | Solution | | ------------------------------------------ | -------------------------------------- | ------------------------------------------------------------- | | WhatsApp messages not triggering workflow | Wrong webhook URL or inactive workflow | Ensure webhook is correct & activate workflow | | AI replies are empty | Missing OpenAI credentials | Add OpenAI API key to all AI nodes | | Vector store not populated | Manual trigger not executed | Run the Test Workflow trigger once | | PDF extraction returns blank text | PDF is image-based | Use OCR before text splitting | | “Unsupported message type” always triggers | Message type filter misconfigured | Check conditions in Handle Message Types | | AI not using brochure data | VectorStore tool not linked properly | Check connections between Embeddings → VectorStore → AI Agent | Need Help with Support & Extensions? If you need help setting up, customizing or extending this workflow, feel free to reach out to our n8n automation developers at WeblineIndia. We can help with Custom WhatsApp automation workflows AI-powered product catalog systems Integrating CRM, ERP or eCommerce platforms Building advanced LangChain-powered n8n automations Deploying scalable vector stores (Qdrant/Pinecone) And so much more.

How It Works Automated daily scraping of competitor websites, pricing pages, job postings, and press releases feeds into an AI analyzer powered by OpenAI or Claude to extract trends, insights, and key metrics. The analyzed results are stored in Google Sheets for historical tracking and longitudinal comparison, and are automatically shared with stakeholders via email or WhatsApp. This workflow eliminates manual competitive research, enabling product teams and executives to monitor market movements efficiently and make timely, data-driven decisions. Setup Steps Configure the daily schedule trigger. Define competitor URLs using workflow variables. Add and configure the OpenAI or Claude API key. Authenticate Google Sheets using the appropriate credentials. Connect Gmail and WhatsApp Business API tokens. Test each scraper individually before enabling full automation. Prerequisites OpenAI/Claude API account, Google Sheets access, Gmail account, WhatsApp Business API, web scraping enabled Use Cases Market share monitoring, pricing strategy updates, competitor talent movement tracking, industry trend reports Customization Modify scrape targets, adjust AI prompt for different metrics, change alert frequency Benefits Real-time competitive visibility, reduced manual research 15+ hours/week, faster decision-making

Who is this for? This workflow is for healthcare professionals, consultants, coaches, and service businesses who want to completely automate their appointment booking system via WhatsApp — without manual intervention for reservations, availability checks, or cancellation management. What problem is this workflow solving? / Use case Managing appointments manually via WhatsApp is extremely time-consuming: checking availability, confirmations, rescheduling, cancellations. This workflow automates the entire process — from initial request to final confirmation — allowing your clients to book, modify, or cancel appointments 24/7, in natural language, directly via WhatsApp. What this workflow does Processes multi-modal messages (text, audio, images) from WhatsApp Business API Detects message type and routes to appropriate processing (Whisper for audio, GPT-4 Vision for images) Uses AI Agent with 5 Cal.com tools to manage complete appointment lifecycle Checks real-time availability in your Cal.com calendar Books appointments autonomously without human intervention Handles cancellations and rescheduling requests Maintains conversation context with Simple Memory for natural exchanges Formats responses with Unicode bold for better WhatsApp readability Sends automated replies directly to the client The result: a fully automated 24/7 appointment management system via WhatsApp. Setup WhatsApp Business API Connect your WhatsApp Business API account in n8n. Set up the webhook in Facebook Developer Console (Webhook → Messages → Subscribe). Add your phone_number_id and access token credentials. Cal.com Create a Cal.com account and configure your calendar. Generate an API Key from Cal.com settings. Set up your event types (duration, availability, pricing). Add your Cal.com API credentials in n8n. OpenAI Get an OpenAI API key (for GPT-4, Whisper, and Vision). Add your OpenAI credentials in n8n. The workflow uses GPT-4 for conversation, Whisper for audio transcription, and GPT-4 Vision for image analysis. Customize the AI Agent Edit the System Message to define your agent's personality, tone, and business context. Adjust timezone in tool parameters (default: Europe/Paris). Configure event type IDs for different appointment types. Test & activate Test with different message types (text, audio, image) from WhatsApp. Verify appointments are created correctly in Cal.com. Switch to production mode and activate the workflow. This workflow helps you build a fully autonomous AI booking assistant, transforming WhatsApp into a 24/7 appointment management system. Need help customizing? Contact me for consulting and support: LinkedIn / Youtube

Description How it works This powerful workflow helps businesses and freelancers automatically manage invoices received on WhatsApp. It detects new messages, downloads attached invoices, extracts key data using OCR (Optical Character Recognition), summarizes the details with AI, updates Google Sheets for record-keeping, saves files to Google Drive, and instantly replies with a clean summary message all without manual effort. Perfect for small businesses, agencies, accountants, and freelancers who regularly receive invoices via WhatsApp. Say goodbye to manual data entry and hello to effortless automation. Set up steps Setup takes around 10–15 minutes: Connect your WhatsApp Cloud API to trigger incoming messages. Add your OCR.Space API key to extract invoice text. Link your Google Sheets and Google Drive accounts for data logging and storage. Enter your OpenAI API key for AI-based summarization. Import the template, test once, and you’re ready to automate your invoice workflow. Why use this workflow Save hours of manual data entry Keep all invoices safely stored and organized in Drive Get instant summaries directly in WhatsApp Improve efficiency for client billing, and expense tracking.

Overview This workflow automates your entire sales outreach process across LinkedIn, Email, and WhatsApp using AI to create hyper-personalized messages for each prospect. Instead of spending hours crafting individual messages, the workflow analyzes your lead data and generates customized connection requests, emails, and WhatsApp messages that feel genuinely personal and researched. The workflow includes a built-in approval mechanism, so you can review all AI-generated messages before they're sent, ensuring quality control while still saving massive amounts of time. How It Works The workflow follows a seven-step process: Step 1: Data Collection The workflow starts by reading your lead data from a Google Sheet. Your sheet should contain information about each prospect including their name, title, company, industry, technologies they use, and any other relevant details that can be used for personalization. Step 2: Batch Processing To prevent overwhelming APIs and ensure smooth operation, the workflow processes leads in batches. Each lead's complete data is prepared and formatted for the AI agent to analyze. Step 3: AI Personalization This is where the magic happens. The AI agent receives all the prospect data and generates three distinct messages: A LinkedIn connection request (under 300 characters) that references their specific role, company, or industry A professional HTML email that demonstrates you've researched their business and explains how you can help A casual WhatsApp message that's friendly and approachable The AI is instructed to make these messages sound completely human, never generic or templated. Step 4: Data Cleanup and Storage The AI's output is parsed and cleaned up, then written back to your Google Sheet in separate columns. This creates a permanent record of all generated messages for your review. Step 5: Manual Approval Before anything gets sent, you receive an email asking for your approval. You can review all the generated messages in your Google Sheet, make any edits if needed, and then approve or reject the batch. This ensures you maintain full control over what goes out. Step 6: LinkedIn Automation Once approved, the workflow triggers your Phantombuster agent to send LinkedIn connection requests using the AI-generated messages. Phantombuster handles the actual LinkedIn interaction safely within their platform's limits. Step 7: Email and Notification Delivery Finally, the workflow sends out the personalized emails via Gmail and optionally notifies you via Telegram for each message sent. This happens sequentially to respect rate limits and maintain deliverability. Setup Requirements Before you can use this workflow, you'll need to set up several accounts and gather credentials: Essential Services: An n8n instance (cloud or self-hosted) A Google account with Google Sheets access A Gmail account for sending emails An OpenAI account with API access (for the AI agent) Phantombuster account (for LinkedIn automation) Optional Services: Telegram account and bot (for notifications) Credentials You'll Need: Google Sheets OAuth2 credentials Gmail OAuth2 credentials OpenAI API key Phantombuster API key and agent ID Telegram bot token and chat ID (if using notifications) How to Use This Workflow Initial Setup: Import this workflow into your n8n instance Add all required credentials in n8n's credential manager Create your Google Sheet with the following columns at minimum: First Name, Last Name, Title, Company Name, Personal Email, Industry, Website. Add three additional columns for output: Connection, AI Email, AI Whatsapp Message Copy your Google Sheet ID from the URL and update it in all Google Sheets nodes Open the AI Agent node and update the prompt with your personal information: your name, title, email, and LinkedIn URL Update the email addresses in the Gmail nodes to your actual email addresses Configure your Phantombuster agent for LinkedIn and add the API key and agent ID Running the Workflow: Add your lead data to the Google Sheet (you can start with just 2-3 leads for testing) Click "Execute Workflow" in n8n to start the process Wait for the AI to generate messages (this takes a few seconds per lead) Check your email for the approval request Review the AI-generated messages in your Google Sheet Reply to the approval email with your decision If approved, the workflow will automatically send LinkedIn requests, emails, and WhatsApp messages Best Practices: Start small. Process 5-10 leads at a time initially to test the quality of AI-generated messages and ensure everything works correctly. Once you're confident in the output, you can scale up to larger batches. Monitor your results. Keep track of response rates in your Google Sheet and adjust the AI prompt if certain types of messages aren't performing well. Respect rate limits. Gmail allows 100-500 emails per day depending on your account type, and LinkedIn has strict limits on connection requests (typically 100 per week through automation tools). Stay well within these limits to avoid account restrictions. Customizing This Workflow The workflow is designed to be highly customizable to fit your specific use case: Personalizing the AI Prompt: The most important customization is in the AI Agent node's prompt. You can modify it to: Emphasize different aspects of your value proposition Change the tone from formal to casual or vice versa Include specific pain points relevant to your target industry Add your company's unique selling points Adjust message length and structure Modifying the Output: You can change what the AI generates by editing the prompt. For example, you might want: Different message types (Twitter DMs instead of WhatsApp) Multiple email variations for A/B testing Follow-up message sequences Industry-specific templates Adding Features: The workflow can be extended with additional nodes: Add time delays between sends to appear more natural Include condition checks to segment leads by industry or company size Connect to your CRM to automatically log activities Add sentiment analysis to filter out negative-sounding messages Implement response tracking by monitoring your inbox Changing Tools: If you prefer different services, you can swap out nodes: Replace Phantombuster with other LinkedIn automation tools Use SendGrid or Mailgun instead of Gmail for higher volume Add Slack notifications instead of Telegram Connect to WhatsApp Business API for official messaging Data Source Alternatives: Instead of Google Sheets, you could: Connect directly to your CRM (HubSpot, Salesforce, Pipedrive) Use Airtable as your database Pull data from CSV files uploaded to cloud storage Integrate with lead generation tools like Apollo or Hunter Tips for Success The quality of your AI-generated messages depends heavily on the data you provide. The more information you have about each prospect (their role, company size, technologies used, recent news, pain points), the more personalized and effective the messages will be. Regularly review and refine your AI prompt based on the responses you're getting. If prospects aren't responding, your messages might be too sales-focused or not personal enough. Adjust the prompt to make messages feel more consultative and helpful. Don't send to your entire list at once. Even with approval gates, it's wise to test with small batches, measure results, iterate on your approach, and then scale up gradually. Always comply with email and LinkedIn best practices. Never spam, always provide value in your outreach, respect people's time and privacy, and make it easy for them to opt out if they're not interested. This workflow is a powerful tool that can save you hours of work while actually improving the quality of your outreach through AI-powered personalization. Use it responsibly and watch your response rates improve.