Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore

What happened

Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore, AWS Machine Learning Blog announced. Learn how to build a Strands-based multi-agent supply chain decisioning system and evaluate it with Amazon Bedrock AgentCore Evaluations using built-in, custom, and explainability evaluators. A critical challenge that emerges as multi-agent systems move from experimentation to production is making sure that these systems are consistently helpful, accurate, and explainable in real-world scenarios.

Enterprises are increasingly adopting multi-agent systems to solve complex, real-world problems that require reasoning across data sources, tools, and business constraints. From supply chain planning to financial analysis and customer operations, these systems go beyond simple question answering.

They coordinate multiple specialized agents to make decisions, execute workflows, and generate actionable recommendations. Amazon Bedrock AgentCore is a platform to build, connect, and optimize agents at scale, with any framework or model.