Generative AI systems are being increasingly utilized in high-stakes environments, including health care, finance, and legal services. While these systems can accelerate workflows and increase access to critical information, they may also produce hallucinations (outputs that are incorrect, inconsistent, or entirely fabricated). In sensitive domains, such responses can result in compliance issues or lead to actual harm in the real world.
To help address these risks, Amazon Bedrock Guardrails introduces Automated Reasoning (AR) checks. Automated Reasoning uses mathematical logic to validate model outputs against predefined rules, ensuring responses remain within safe and allowable constraints. By embedding AR into your applications, you can block unsafe content before it reaches users, reduce hallucinations, and maintain adherence to regulatory and organizational policies.
In this Cloud Lab, you’ll work through a medical risk-assessment scenario in which patient information is classified as “High,” “Medium,” or “Low” risk. Using the AWS Management Console, you’ll configure an Automated Reasoning policy, test it with sample data, and integrate it into a guardrail. You’ll then deploy a sample chatbot-style application to observe how AR checks operate in practice.
By the end of this Cloud Lab, you’ll understand the principles of Automated Reasoning and know how to apply them to enhance the safety and reliability of generative AI applications.
