What is Retrieval Augmented Generation (RAG)?

Retrieval Augmented Generation is a pipeline framework that retrieves information via an external discovery system, enhancing the knowledge retrieval process for large language models. 

Generative AI and large language models (LLMs) are emerging as some of today’s most transformative workplace technologies – however, many solutions struggle with knowledge retrieval. Retrieval Augmented Generation addresses this issue by separating the knowledge retrieval from the generation process.

Learn more about what it takes to make RAG work and how it unlocks the full potential of generative AI in this free 2-pager.

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