Amazon Bedrock AgentCore Evaluations can now integrate with decision models via code-based evaluators to score artificial intelligence agents across their development and production lifecycles. AgentCore Evaluations includes 15 built-in evaluators as well as custom options, such as an LLM-as-a-judge or code-based logic executed in AWS Lambda functions. Through these Lambda functions, developers can connect external systems and APIs, including decision models, to assess whether an agent stays on policy, provides gr…
Key points
Integrating decision models enables teams to systematically verify that AI agents adhere…: Integrating decision models enables teams to systematically verify that AI agents adhere to safety policies and execute grounded tool calls.
Both supported backends handle binary queries, multiple-choice questions with up to 255 o…: Both supported backends handle binary queries, multiple-choice questions with up to 255 options, and ordered scores spanning two to 10 levels.
Organizations can implement these specialized models as initial screening filters to flag…: Organizations can implement these specialized models as initial screening filters to flag specific conversational turns for deeper review.
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Artificial Intelligence
Use decision models with Amazon Bedrock AgentCore Evaluations
Some of the questions you ask when evaluating an agent are narrow and repeatable. Did this response stay on policy? Is this tool call safe to approve? Does this answer match the retrieved context? Decision models answer exactly that kind of question. They take a structured state and a fixed set of allowed answers and return a calibrated probability over them, rather than free-form text whose confidence drifts from run to run. That makes them a strong fit for the scoring step in an agent evaluation, where you want a label and a number you can threshold and trust.
Amazon Bedrock AgentCore Evaluations, a capability of Amazon Bedrock AgentCore, scores an agent through its entire lifecycle, on demand during development, in batch jobs against stored sessions, and online against production traffic. Alongside 15 built-in evaluators, AgentCore Evaluations supports custom evaluators that you define as either an LLM-as-a-judge or a code-based evaluator. Custom LLM-as-a-judge evaluators apply your instructions and rating scale with a model in Amazon Bedrock. Code-based evaluators run your…
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