đź’¬ Voice AI customer support for WooCommerce using VAPI, GPT-4o & Gemini with RAG

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Description

This workflow integrates a Retrieval-Augmented Generation (RAG) system with a post-sales AI agent for WooCommerce. It combines vector-based search (Qdrant + OpenAI embeddings) with LLMs (Google Gemini and GPT-4o-mini) to provide accurate and contextual responses.

Both systems are connected to VAPI webhooks, making the workflow usable in a voice AI assistant via Twilio phone numbers.

The workflow receives JSON payloads from VAPI via webhooks, processes the request through the appropriate chain (Agent or RAG), and sends a structured response back to VAPI to be read out to the user.


Advantages


How it Works

It has two main components:

  1. RAG System (Knowledge Retrieval & Q&A)

    • Uses OpenAI embeddings to store documents in Qdrant.
    • Retrieves relevant context with a Vector Store Retriever.
    • Sends the information to a Question & Answer Chain powered by Google Gemini.
    • Returns precise, context-based answers to user queries via webhook.
  2. Post-Sales Customer Support Agent

    • Acts as a WooCommerce virtual assistant to:

      • Retrieve customer orders (get_order, get_orders).
      • Get user profiles (get_user).
      • Provide shipment tracking (get_tracking) using YITH WooCommerce Order Tracking plugin.
    • Enforces strict verification rules: customer email must match the order before disclosing details.

    • Communicates professionally, providing clear and secure customer support.

    • Integrates with GPT-4o-mini for natural conversation flow.


Set Up Steps

To implement this workflow, follow these three main steps:

1. Infrastructure & Credentials Setup in n8n:

2. Workflow Activation in n8n:

3. VAPI Configuration:


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đź”— Nodes Used

HTTP Request, Webhook, Execute Workflow Trigger, AI Agent, Question and Answer Chain, Embeddings OpenAI

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup