Best AI conversation analytics tools (2026): classify agent traffic at scale

AI conversation analytics is a practice that involves classifying and grouping every interaction an AI agent has with users to identify trends and recurring patterns in production traffic. This process aims to improve the understanding of user tasks, sentiment, and failure patterns, which aids in prioritizing issues and converting repeated failures into evaluation cases before subsequent releases. Braintrust, a leading platform in this area, utilizes its Topics feature to automatically classify conversations by task, sentiment, and issues without requiring predefined classifiers, transforming production conversations into structured datasets for evaluation. This capability allows teams to filter logs, inspect source conversations, and convert recurring patterns into datasets, online scorers, and review queues, thereby enhancing the quality and reliability of AI systems. Other tools like Galileo, HoneyHive, Datadog, and Langfuse offer varying features focused on observability, tracing, and evaluation but may require more setup or focus on different aspects like runtime protection or open-source deployment.

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