Build custom code-based evaluators in Amazon Bedrock AgentCore

2026-05-18 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Robotics & Autonomous Systems · Depth: Intermediate, long

Summary

Amazon Bedrock AgentCore Evaluations now supports custom code-based evaluators, enabling developers to implement deterministic quality checks for agentic applications using AWS Lambda functions. This feature addresses domain-specific requirements in areas like financial services, where LLM-as-a-Judge evaluations may be insufficient or costly for tasks such as validating JSON schemas, ensuring numerical accuracy, enforcing workflow compliance, and detecting Personally Identifiable Information (PII). These custom evaluators can be registered at TRACE, TOOL_CALL, or SESSION levels and operate in both on-demand mode for development and CI/CD gating, and online mode for continuous production monitoring. The article demonstrates this capability with a Market Trends Agent example, showcasing four Lambda-based evaluators for schema validation, stock price drift, workflow contract, and PII leakage detection, integrating with CloudWatch for metrics and alarms.

Key takeaway

For AI Engineers building production-ready agents, integrating custom code-based evaluators into Amazon Bedrock AgentCore is crucial for enforcing strict, deterministic quality standards. You should identify critical structural, numerical, and compliance requirements that LLM-as-a-Judge cannot reliably handle and implement these checks as AWS Lambda functions. This approach ensures agent reliability beyond "sounds right" to "contract-verified," providing robust validation for sensitive applications and enabling automated CI/CD gates and continuous production monitoring.

Key insights

Custom code-based evaluators in Amazon Bedrock AgentCore enable deterministic, domain-specific quality checks for agentic applications.

Principles

• Deterministic checks complement LLM-as-a-Judge.
• Tailor evaluation logic with AWS Lambda.
• Use OTel spans for agent session context.

Method

Register AWS Lambda functions as custom evaluators in AgentCore, defining scoring logic for specific quality dimensions. Deploy and test in on-demand mode, then promote to online evaluation for continuous monitoring, integrating with CloudWatch for metrics and alarms.

In practice

• Validate tool outputs against JSON schemas.
• Verify numerical accuracy against external sources.
• Enforce multi-step workflow contracts.

Topics

• Amazon Bedrock AgentCore
• Custom Code Evaluators
• AWS Lambda
• Agent Quality Evaluation
• CI/CD Pipelines

Code references

• aws-samples/amazon-bedrock-agentcore-samples
• awslabs/agentcore-samples

Best for: AI Engineer, MLOps Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.