Amazon Bedrock Knowledge Bases allows you to build scalable Retrieval Augmented Generation (RAG) applications for analyzing private data using AWS and third-party language models and vector stores, enabling natural question answering by retrieving relevant context from the data.

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<p>This article discusses how to use Amazon Bedrock Knowledge Bases for drug discovery through a Retrieval Augmented Generation (RAG) workflow.</p>
<p>Specifically, the article covers:</p>
<ul>
<li>An overview of Amazon Bedrock Knowledge Bases and its capabilities for building RAG applications</li>
<li>Steps to create a Knowledge Base in the Amazon Bedrock console</li>
<li>Querying the Knowledge Base using the RetrieveAndGenerate API, Retrieve API, and LangChain integration</li>
<li>A sample use case of analyzing an unstructured clinical trial dataset to generate insights</li>
<li>Clean-up instructions to avoid incurring additional charges</li>
</ul>
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Use RAG for drug discovery with Amazon Bedrock Knowledge Bases

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