RAG

RAG stands for Retrieval-Augmented Generation: a technique that makes an AI system search a trusted knowledge base — docs, FAQs, prices, policies — before it writes an answer.

Instead of relying only on what a large language model memorized during training, RAG retrieves relevant chunks in real time and feeds them into the prompt. That reduces guesswork and hallucinations when the question is about your business. It pairs well with chatbots and AI agents that must stay accurate.

A real-life example of RAG

Without RAG, asking “What’s our refund window?” is like an open-book test with no book — the model may invent a policy. With RAG, the system finds your refund page first, then answers from that text. Same idea as letting a new hire check the handbook before they reply to a customer.

RAG doesn’t replace good content or permissions; it needs clean, up-to-date sources. Dive into the full explanation in How Does AI Know About My Business? (What Is RAG).