Conclusion

The architectures presented in this guide offer a comprehensive framework for organizations that use AWS services to take advantage of generative AI capabilities securely and efficiently. These architectures combine the fully managed functionality of Amazon Bedrock with security best practices to provide a solid foundation for integrating generative AI into traditional cloud workloads and organizational processes.

The specific capabilities covered—foundation model inference, model customization, retrieval augmented generation, tool integration, autonomous agents, and end-user applications—address a wide range of potential applications and scenarios. This guidance equips organizations with the necessary understanding of Amazon Bedrock services and their inherent and configurable security controls. With this knowledge, organizations can make informed decisions tailored to their unique infrastructure, applications, and security requirements.

By implementing the security controls described across all six capabilities, organizations can build generative AI applications that maintain strong security postures while delivering innovative functionality. The separation of concerns between Application and Generative AI accounts, combined with defense-in-depth security controls at every layer, provides the foundation for secure, scalable generative AI deployments.