AI

Retrieval-augmented generation (RAG) is an AI architecture that combines a large language model with an external knowledge base. Instead of relying solely on training data, the model retrieves relevant documents at query time and uses them to generate more accurate, grounded responses. This reduces hallucinations and keeps answers current without retraining.