Retrieval Augmented Generation (RAG) enhances Large Language Models (LLMs) by providing real-time access to external data, improving response accuracy and relevance. RAG reduces hallucinations, facilitates quick updates without retraining, and supports dynamic, contextually aware applications. This approach is vital for areas requiring reliable and current information, such as customer support and finance.