RAG (Retrieval-Augmented Generation)

Retrieval-Augmented Generation (RAG) combines large language models with an external search or retrieval mechanism to pull in relevant documents or data before formulating responses. In enterprise AI, RAG allows systems to provide more accurate and context-rich answers by grounding outputs in up-to-date, factual knowledge from reference sources.