This customer support chatbot uses Retrieval-Augmented Generation (RAG) architecture to provide accurate, context-aware responses based solely on your business documentation. Unlike generic chatbots that may hallucinate or provide incorrect information, this system grounds all responses in your actual business knowledge base.
The bot indexes your documentation, FAQs, product information, and support materials into a vector database using Supabase pgvector. When a customer asks a question, it retrieves the most relevant information from your documents and generates a natural, helpful response.
The system includes streaming responses for a ChatGPT-like experience and gracefully handles questions outside its knowledge scope by admitting when it doesn't have the answer and offering to connect the customer with human support.