RAG is a complex technique that relies on: The quality of data fed into it The effectiveness of search retrieval Data security The ability to cite the sources of generative AI responses in order to fine tune the results In addition, choosing the right generative AI or large language model (LLM) in a fast moving ecosystem can pose challenges for organizations. And the costs, performance, and scalability associated with RAG can hinder the speed at which enterprises launch applications into production.