Retrieval-Augmented Generation (RAG)

Definition

An AI architecture that combines a large language model with an external knowledge retrieval system, enabling the model to ground its responses in verified, up-to-date information rather than relying solely on its training data. RAG reduces hallucination risk, improves factual accuracy, and allows organisations to deploy AI systems that reference proprietary knowledge bases without retraining the underlying model.