Build reliable AI agents with Amazon Bedrock AgentCore Evaluations

Amazon has launched Bedrock AgentCore Evaluations, a fully managed service designed to solve the critical reliability gap in AI agent deployment. Traditional software testing fails with non-deterministic large language models (LLMs), where the same query can produce different tool calls and outputs across multiple runs. This service introduces systematic measurement across these variations, allowing teams to understand what typically happens rather than just what can happen in isolated tests.

AgentCore Evaluations handles the entire evaluation infrastructure—including scoring models, inference capacity, data pipelines, and visualization dashboards—that previously required significant developer overhead. The service measures agent accuracy across multiple quality dimensions: correct tool selection, valid parameter usage, accurate responses, and overall helpfulness. By providing both development and production evaluation approaches, it enables continuous testing cycles where failures become new test cases, creating a feedback loop for iterative improvement.

The service, first previewed at AWS re:Invent 2025 and now generally available, addresses the fundamental challenge that has plagued AI agent deployment: the disconnect between demo performance and real-world reliability. Without systematic evaluation, teams face unpredictable failure modes, inconsistent responses, and wasted API costs from manual debugging. AgentCore Evaluations shifts this paradigm by providing the infrastructure needed to prove agent performance rather than just hoping it works.