Retrieval Augmented Generation (RAG) — an architecture pattern that combines LLMs with backend information retrieval from other information sources. This approach can help overcome some of the most significant limitations of LLMs, such as knowledge limited to the scope of training data, lack of relevant context from enterprise data, and data that is not fresh or outdated.