Retrieval-augmented generation (RAG) is an AI architecture that enhances LLM accuracy by dynamically retrieving relevant, up-to-date information from external knowledge sources RAG significantly reduces hallucinations and improves response accuracy in critical domains like healthcare (96% diagnostic accuracy) and legal (38-115% productivity gains)