Retrieval-Augmented Generation (RAG)

RAG systems retrieve relevant documents from an internal knowledge base at query time and feed them into the model's context window, so answers are grounded in verifiable source material rather than the model's parametric memory. It is the dominant enterprise pattern for reducing hallucination risk in customer support, legal, and internal knowledge-management use cases.

Definitions are written for enterprise AI governance context, not a formal legal standard. Suggest a correction →