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

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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.

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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.