By fetching data from the organization’s internal or proprietary sources, Retrieval Augmented Generation (RAG) extends the capabilities of FMs to specific domains, without needing to retrain the model. It is a cost-effective approach to improving model output so it remains relevant, accurate, and useful in various contexts.

Knowledge Bases for Amazon Bedrock is a fully managed capability that helps you implement the entire RAG workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows. With MongoDB Atlas vector store integration, you can build RAG solutions to securely connect your organization’s private data sources to FMs in Amazon Bedrock.

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