This workflow is a complete AI-powered customer support automation for e-commerce businesses.
This workflow is a complete AI-powered customer support automation for e-commerce businesses. The system allows customers to interact with an AI assistant directly through WhatsApp. This chatbot can: Answer customer questions in real time Retrieve order information from WooCommerce Search products and provide recommendations Access company policies and FAQs using RAG (Retrieval-Augmented Generation) Escalate conversations to human support when necessary Maintain conversation memory for contextual interactions Apply AI guardrails for safer conversations Key Advantages 1. ✅ Fully Automated Customer Support The workflow dramatically reduces manual customer support workload by automating: FAQs Order tracking Product inquiries Return policy questions Technical troubleshooting This enables 24/7 support availability without human intervention. 2. ✅ Native WhatsApp Integration Using Whapi, customers can communicate through WhatsApp — one of the most widely used messaging platforms globally. 3. ✅ AI-Powered Product Assistance The assistant can: Search products in WooCommerce Compare items Recommend products Check stock availability Provide real-time pricing This transforms the chatbot into an intelligent sales assistant, increasing conversion opportunities. 4. ✅ RAG Knowledge Base with Qdrant The workflow uses Retrieval-Augmented Generation (RAG) powered by Qdrant vector search. 5. ✅ Human Escalation System When the AI cannot solve an issue, the workflow automatically escalates the conversation to human support via Gmail. 6. ✅ Multi-Model AI Architecture The workflow combines: Google Gemini for conversational reasoning OpenAI embeddings for semantic retrieval 7. ✅ Persistent Conversation Memory The Window Buffer Memory node maintains contextual conversations. 8. ✅ Built-In Guardrails & Security The workflow includes AI Guardrails to: Filter inappropriate content Block unsafe requests Prevent policy violations Improve AI reliability This is essential for production-ready AI assistants. 9. ✅Real-Time WooCommerce Integration The chatbot interacts directly with WooCommerce APIs to: Retrieve customer profiles Access order history Check shipment status Query products This provides live data instead of static responses. 10. ✅ Modular & Scalable Architecture The workflow is highly modular: Easily customizable Extendable with new tools Compatible with additional APIs Scalable for large e-commerce operations New AI tools or integrations can be added without redesigning the entire system. Ideal Use Cases This workflow is ideal for: E-commerce stores Fashion brands Electronics retailers Customer support automation AI sales assistants WhatsApp commerce Technical support automation Multilingual support systems This workflow represents a production-ready AI customer support system capable of combining conversational AI, semantic search, real-time e-commerce operations, and human escalation into a single automated pipeline. How it works WhatsApp message reception The workflow starts when a WhatsApp message is received via the Get WhatsApp webhook (Whapi). It checks if the message is of type text — if not, it replies with a message saying only text is supported. Guardrails & policy check The message passes through a Guardrails node that filters inappropriate content or policy violations. If the message violates policies, a rejection reply is sent. Customer support AI Agent The message is passed to an AI Agent (powered by Google Gemini or OpenAI). The agent has access to: Memory (Window Buffer Memory) to keep conversation context. Tools for: Retrieving company knowledge via rag_search (from Qdrant). Fetching WooCommerce orders, products, and customers. Performing calculations. Escalating to human support via Gmail. The agent follows a detailed system prompt covering product info, order assistance, technical support, and escalation logic. Response normalization & sending The agent's raw output is cleaned (newlines/tabs escaped) via a Code node. The cleaned response is sent back to the customer via Whapi (Send WhatsApp). Knowledge base vectorization (separate flow) A separate part of the workflow (triggered manually) loads documents from Google Drive, splits them into chunks, generates embeddings via OpenAI, and stores them in Qdrant for semantic search. Set up steps Configure external services & credentials Whapi: Sign up (FREE TRIAL available), get API credentials, and set the webhook URL in Whapi settings to point to your n8n webhook. OpenAI: Create an API key for embeddings and chat model (or use Google Gemini). Qdrant: Set up a Qdrant instance (e.g., on Hetzner) and create API credentials. Google Drive: Authenticate to access document folders. WooCommerce: Generate API keys for order/product/customer retrieval. Gmail: Authenticate for human support escalation. Create Qdrant collection Run the Create collection HTTP request node (update QDRANTURL and COLLECTION name). Upload & vectorize documents Place your knowledge base files (PDFs, text, Google Docs) in a Google Drive folder. Set the folder ID in the Get folder node. Run the manual trigger to load, split, embed, and store documents into Qdrant. Configure the AI Agent Set the system prompt (already provided in the E-Commerce Customer Support AI Agent node). Choose the language model (Gemini or OpenAI) and connect credentials. Ensure all tools (rag_search, WooCommerce nodes, calculator, Gmail) are enabled and properly connected. Set webhook & activate workflow Copy the webhook URL from the Get WhatsApp node. Paste it into your Whapi dashboard as the incoming message webhook. Toggle the workflow to active. 👉 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. An n8n automation workflow template by Davide Boizza.
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