Revolutionizing Generative AI Applications with Amazon Bedrock Agents and Verified Permissions
Amazon Bedrock Agents are changing the game for generative AI applications by enabling them to perform complex multistep tasks across various company systems and data sources. These agents leverage the power of the foundation model (FM) to analyze and orchestrate tasks, ensuring they are executed in the correct logical sequence. By automatically interacting with company systems and processes through APIs, these agents streamline workflows and provide real-time insights to users.
Empowering Innovation with Amazon Bedrock Agents
Customers can now build innovative generative AI applications that intelligently orchestrate their workflows using Amazon Bedrock Agents. One of the key challenges faced by customers is implementing fine-grained access controls to ensure that application workflows operate only on authorized data based on user entitlements. This can be a complex and time-consuming task if done manually. However, with Amazon Verified Permissions, customers can seamlessly integrate contextually aware access controls into their workflows, enhancing security and efficiency.
Designing Fine-Grained Access Controls
In a recent use case, we demonstrated how to design fine-grained access controls using Verified Permissions for a generative AI application focused on answering questions about insurance claims. By leveraging Amazon Bedrock Agents, users can interact with the application using textual prompts and receive accurate responses based on their permissions and access rights.
Solution Overview
Our solution involves using Amazon DynamoDB to store claims records and building a chat-based application that provides information about these claims. Users, such as claims administrators and adjusters, can perform actions like listing open claims, viewing claim details, and updating claim statuses. By incorporating fine-grained access controls, we ensure that each user can only access information relevant to their role and permissions.
Entities Design Considerations
When designing fine-grained data access controls, it is essential to consider the entities and attributes that play a role in authorization decisions. In our application, we focus on entities such as Applications, Claims, Users, and Roles, each with specific attributes that govern access permissions. By leveraging role-based access control (RBAC) and attribute-based access control (ABAC), we can effectively manage and enforce access policies.
Fine-Grained Authorization: Policy Design
Verified Permissions provides a robust policy design framework that enables users to define and enforce access policies based on roles, actions, and resources. By creating policies that permit or forbid specific actions on resources, users can maintain a secure and compliant environment. Check out the policy examples provided in this post for various access control scenarios.
Conclusion
By combining the capabilities of Amazon Bedrock Agents and Verified Permissions, organizations can build secure and efficient generative AI applications that deliver personalized and contextual responses to users. This solution provides a scalable and flexible approach to managing access controls, ensuring data security and compliance. Give it a try and experience the power of fine-grained access controls in your AI workflows!
About the Authors
Ram Vittal, Samantha Wylatowska, Anil Nadiminti, Michael Daniels, and Maira Ladeira Tanke are experienced professionals in the field of AI/ML and cloud computing, bringing a wealth of expertise to the table. Their passion for innovation and dedication to empowering customers through technology shines through in their work.