An LLM is trained up to a cutoff date. It does not know your internal documents. It does not know what happened yesterday. Retrieval-Augmented Generation fixes this: before generation, the system retrieves relevant snippets from a knowledge base and puts them into the context. The model sees context plus question — and answers grounded in specific documents, not only in weights. This is the dominant pattern for production LLM apps.