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Deploy RAG-based AI agents using Amazon Bedrock

Scalable, data-driven AI agents enable faster, more intuitive user interactions for your applications. In this tutorial, you’ll integrate Amazon Bedrock with Pinecone Vector Database to stand up an AI agent using a RAG pipeline in your AWS environment.

Learn how to configure a Pinecone index, sync data to an Amazon Bedrock Knowledge Base, and expose your agent via API for real-time interaction. See how quickly you can deliver smarter experiences using your own data.

Use RAG to power responsive, data-driven agents ›

In collaboration with

Pinecone

Try Pinecone Vector Database for free in AWS Marketplace.

Get started in AWS Marketplace ›

About AWS Marketplace

Visit AWS Marketplace for help finding the best solutions for your use case and add new capabilities to your tech stack with your AWS account:

Easily add capabilities into your AWS environment from category-leading AWS partners with free trials
Avoid upfront license fees and pay only for what you use, consolidating billing with your AWS account
Boost performance, security, and scalability while enabling new user experiences

In collaboration with