Your generative AI applications can deliver better responses by incorporating organization-specific data through a technique known as Retrieval Augmented Generation (RAG). However, implementing RAG requires time to configure connections to data sources, manage data ingestion workflows, and write custom code to manage the interactions between the foundation model (FM) and the data sources. Join this session to learn how to make the process much easier using Amazon Bedrock. Based on the user prompt, Amazon Bedrock automatically identifies data sources, retrieves the relevant information, and adds the information to the prompt, thereby giving the FM more information to generate responses. See how it works in this session.

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