Introducing Confident Monitor

Confident AI has introduced Monitor, a production-monitoring tool for AI applications that analyzes millions of incoming agent traces, evaluates them using configurable LLMs or its Jev evaluator, and groups related failures into prioritized issues. Rather than requiring teams to manually sift through traces, the platform aims to identify root causes, provide supporting examples, and suggest fixes tested against failing cases, allowing users to review and apply changes more quickly. Monitor works with existing traces and supports varied agent frameworks, model providers, and architectures without new instrumentation, while integrating insights into existing workflows such as Claude Code for updates on new or worsening problems. The product is positioned as part of Confident AI’s broader quality platform, which includes evaluation, observability, red teaming, annotation workflows, and support for AI use cases including agents, MCP, voice, retrieval-augmented generation, and chatbots.

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