How to Build Accurate WhatsApp Auto-Replies Using n8n and RAG Architecture

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Developers can automate WhatsApp Business API responses by combining n8n workflow automation with Retrieval-Augmented Generation (RAG) to ground replies in verified documentation. The setup involves ingesting FAQ documents into a vector database such as Pinecone or Supabase, then retrieving the most relevant chunks when a user message arrives via webhook. Retrieved context is fed into a large language model like GPT-4o, which is instructed to answer strictly from the provided material to prevent hallucinations. Key tools required include Meta Business Manager, an OpenAI API account, a vector store, and either a cloud server or ngrok to receive webhooks. The architecture is designed to scale customer support without manual intervention while keeping responses accurate and traceable to source documents.

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