Knowledge Bases for Amazon Bedrock

With Knowledge Bases for Amazon Bedrock, you can give FMs and agents contextual information from your company’s private data sources for Retrieval Augmented Generation (RAG) to deliver more relevant, accurate, and customized responses

A formal depiction of a knowledge base's overview

Fully managed support for end-to-end RAG workflow

To equip FMs with up-to-date and proprietary information, organizations use Retrieval Augmented Generation (RAG), a technique that fetches data from company data sources and enriches the prompt to provide more relevant and accurate responses. 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. Alternatively, you can ask questions and summarize data from a single document, without setting up a vector database. You can also have a Session context management is built in, so your app can readily support multi-turn conversations.

screen to create knowledge base and set up data sources

Securely connect FMs and agents to data sources

Simply point to the location of your data in Amazon S3, and Knowledge Bases for Amazon Bedrock automatically fetches the documents from multiple sources, divides them into blocks of text, converts the text into embeddings, and stores the embeddings in your vector database. If you do not have an existing vector database, Amazon Bedrock creates an Amazon OpenSearch Serverless vector store for you. Or you can specify an existing vector store in one of the supported databases, including Amazon OpenSearch Serverless, Pinecone, and Redis Enterprise Cloud, with support for Amazon Aurora and MongoDB coming soon.

Easily retrieve relevant data and augment prompts

You can use the Retrieve API to fetch relevant results for a user query from knowledge bases. The RetrieveAndGenerate API goes one step further by directly using the retrieved results to augment the FM prompt and return the response. You can also add knowledge bases to Agents for Amazon Bedrock to provide contextual information to agents.