What Is Retrieval-Augmented Generation (RAG)? Architecture, Vector Retrieval & Enterprise AI
Retrieval-Augmented Generation (RAG) is an enterprise AI architectural pattern that optimizes large language model outputs by referencing authoritative, verified knowledge bases outside of its training data before generating a response. Rather than relying on static model weights that can hallucinate or become obsolete, RAG anchors responses strictly in organizational documents, API records, and structured databases.