Build custom code-based evaluators in Amazon Bedrock AgentCore | Amazon Web Services
Special thanks to everyone who contributed to this launch: Stephanie Yuan, Lefan Zhang, Ritvika Pillai, Irene Wang, Carter Williams, T.J Ariyawansa, Gitika Jha, Shoaib Javed and the product leadership from Vivek Singh.
Moving prototype agents to production requires measuring quality across multiple dimensions. Amazon Bedrock AgentCore Evaluations provides large language model (LLM)-as-a-Judge checks and extensible code-based evaluators that capture domain-specific requirements you need for assessing your agentic application.
In financial services and specialized domains, the critical quality dimensions often extend beyond language. A market-intelligence agent must quote stock prices within a configurable live band, follow a mandatory broker-identification workflow before accessing financial profiles, return tool outputs that conform to a strict JSON schema, and withhold personally identifiable information (PII). These checks require deterministic code that produces the same result on identical input. They can also be expensive to run with LLM-as-a-Judge when an objective piece of code is the straightforward...
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