Unlocking the Power of Generative AI with Amazon Bedrock Agents

In today’s fast-paced digital landscape, businesses are increasingly leveraging generative AI to streamline operations and enhance user experiences. One of the exciting innovations in this space is Amazon Bedrock Agents, which empower organizations to tackle complex multistep tasks by integrating seamlessly with various data sources and systems.

What Are Amazon Bedrock Agents?

Amazon Bedrock Agents act as intelligent orchestrators that utilize the reasoning capabilities of foundation models (FMs) to break down tasks into logical sequences. By automatically calling necessary APIs, these agents interact with company processes to fulfill user requests. Throughout this journey, they continuously assess if they can move forward with the information available or if additional details are required.

Fine–Grained Access Control Made Easy

A common challenge when developing generative AI applications is implementing fine-grained access controls. Businesses want to ensure that their workflows only operate on authorized data relevant to specific users. Traditionally, this would require hardcoding numerous rules into applications or creating complex authorization systems from scratch.

Here’s where Amazon Verified Permissions comes into play. This scalable permission management service allows developers to externalize authorization components and centralize policy management, making it a breeze to enforce access controls based on user roles, contexts, and actions.

A Closer Look: Designing a Claims Processing Application

Consider a scenario in the insurance sector where we wish to develop a generative AI application using Amazon Bedrock Agents to answer inquiries about insurance claims. In this example, we have two types of users: claims administrators and claims adjusters. Both groups can list open claims; however, only claims adjusters can access detailed records and make updates.

Access Control Requirements:

• Claims Administrators: Can list claims across various regions but cannot read individual claim details.
• Claims Adjusters: Can list claims for their designated region and have the ability to read and update records they own.

This differentiation is crucial for maintaining data security and ensuring that sensitive claim information is only accessible to authorized personnel.

Practical Application Architecture

Imagine a chat-based assistant designed to help users quickly access information about their claims. Here’s how it works:

1. User Authentication: Users access the application and authenticate via Amazon Cognito, receiving ID and access tokens.
2. Claim Requests: When a user requests to "list their open claims,” the app sends this request along with their tokens to the Claims API Gateway.
3. Authorization: The Claims API Gateway validates the access tokens, sending verified requests onward to the Claims Proxy.
4. Action Execution: The Claims Proxy invokes the Amazon Bedrock agent, which uses the Claude model to process the request and respond accordingly.

By integrating Verified Permissions, the system creates a well-rounded security framework while allowing both administrative roles to efficiently navigate their tasks.

Real-Life Use Case: Claims Administration

Let’s break down how the claims administrator interacts with the system:

• Listing Claims Across Regions: The claims administrator can successfully list claims thanks to the broad permissions associated with their role.
• Attempting to Access Claim Details: If they try to view specific claim details, the system will return a denial, as their role doesn’t permit it.

For the claims adjuster, their journey is also unique:

• Viewing Owned Claims: They can see all claims assigned to them in their region. If they try to access claims outside their jurisdiction, the system will rightfully block that request.

Entities & Policies: The Backbone of Access Control

Designing an effective application begins with a strong entity-relationship diagram (ERD). Our claims application establishes clear relationships between users, claims, and roles. Each user is categorized into roles that dictate their capabilities within the application:

• Claims Administrators: Broad access but no individual claim visibility.
• Claims Adjusters: Restricted access based on region and ownership.

Using Verified Permissions, both role-based access control (RBAC) and attribute-based access control (ABAC) allow precise management of permissions, ensuring users only interact with information relevant to their role and geographical location.

Crafting Effective Policies

Policies dictate whether a user can take specific actions on resources, and they’re determined by evaluating principals, actions, and resources:

• Policy Example: A claims administrator can list claims but cannot view details.
• Deny Policies: Explicitly deny access where necessary, to ensure sensitive data remains secure.

An Engaging User Experience

The architecture accommodates seamless interactions while upholding stringent security measures. Users receive tailored responses that respect their access levels, ensuring a smooth experience while navigating claims data.

Conclusion: Embrace the Future with Amazon Bedrock

The challenges of implementing stringent access controls in agent workflows can be daunting, but by utilizing Amazon Verified Permissions alongside Amazon Bedrock Agents, businesses can build effective, secure generative AI applications that cater to their specific needs.

As you explore these tools, consider how they can revolutionize workflows in your organization. The AI Buzz Hub team is excited to see where these breakthroughs take us. Want to stay in the loop on all things AI? Subscribe to our newsletter or share this article with your fellow enthusiasts.