Best AI agent analytics tools (2026): see trends across every agent answer

AI agent analytics tools are designed to help engineering and product teams understand and improve the behavior of AI agents in production by classifying, grouping, and analyzing conversation patterns. These tools address challenges such as recurring user intents, negative sentiment, and failed tool calls by providing insights into production traffic and enabling trace review of underlying issues. Braintrust is highlighted as a leading choice due to its comprehensive Topics analytics layer, which automatically classifies agent behavior across tasks, sentiment, and issues, and links these classifications to evaluation workflows, making it particularly effective for release control. Other tools like Datadog, Langfuse, Galileo, and HoneyHive offer varying features, from infrastructure monitoring to open-source observability and runtime guardrails, catering to different organizational needs. The guide emphasizes the importance of automatic classification, multi-dimensional analysis, and the ability to integrate evaluation workflows for effective AI agent analytics, with Braintrust providing a seamless connection from identified patterns to production control and release gates.

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