Retrieval-Augmented Generation (RAG)

RAG connects an AI model to external information sources (like documents or databases). The model first retrieves relevant facts (like a "librarian") and then generates a response using that material (like an "author"). It keeps AI answers accurate, up-to-date, and grounded in real data, essential for enterprise use cases.