Retrieval-Augmented Generation (RAG) is a generative AI delivery approach that lets companies integrate their privately-owned internal data with the publicly available external data used to train Large Language Models (LLMs).
Despite its ability to enhance response accuracy, RAG is challenging to design and deploy. Data pros can use this condensed version of the Gartner report to better prepare themselves for RAG.
