Amazon Bedrock is a managed platform on AWS for building generative AI applications and agents. It brings together:

• Leading foundation models (FMs) you can use out of the box.
• Services to deploy and operate agents that can act on behalf of your applications.
• Tools for fine-tuning, safeguarding, and optimizing models so you can adapt them to your use cases.
• Knowledge bases that connect your applications to your latest data.

Because these capabilities are available in one place, teams can move from early experimentation to real-world deployment more quickly, without stitching together multiple tools or managing complex infrastructure themselves.

Amazon Bedrock is designed to shorten the path from proof of concept to production by providing:

• Pre-integrated foundation models, so you can start prototyping without building your own models or pipelines.
• Built-in tools for fine-tuning and optimization, which help you adapt models to your domain as you refine your prototype.
• Safeguarding capabilities to manage responsible use of generative AI as you prepare for real users.
• Knowledge bases that let you connect to your most current data, so your application reflects real business context.
• Operational services for agents, so you can deploy, monitor, and manage AI agents as part of your production stack.

All of this runs on AWS, which provides global infrastructure, security, reliability, and performance, so you can scale from a small pilot to a broader rollout without re-architecting your solution.

Using Amazon Bedrock on AWS lets you reimagine how you build and operate generative AI by combining model choice with cloud capabilities:

• Comprehensive platform: Access leading foundation models, agent services, fine-tuning, safeguarding, optimization tools, and knowledge bases in one environment.
• Built on AWS: You benefit from AWS’s broadly adopted cloud platform, with extensive global infrastructure and a focus on security, reliability, and performance.
• Flexibility and control: Start quickly with managed services, then refine models and connect to your own data as your use cases mature.
• Ecosystem and support: You can tap into AWS resources such as AWS Marketplace, the AWS Partner Network, and the AWS re:Post community for technical questions.

This combination helps teams prototype, iterate, and then operate generative AI applications in production without having to build and maintain all the underlying AI and cloud infrastructure themselves.