performance-monitor

Track token usage across multi-turn AI agent conversations by applying token accounting and cost control monitoring to identify spending drift and govern expenses across complex workflows.

Measure AI agent latency by capturing baseline response times and analyzing tail latency to detect streaming bottlenecks and maintain performance reliability across agent workflows.

Eval framework integration quantifies AI agent quality and consistency by applying evaluation metrics to detect regression risk and measure response improvements across conversations.

Yes, you can configure dashboards and alerts for AI agent performance anomalies to enable proactive incident response and cost governance when token usage or latency spikes occur.

Benchmark AI agent performance when complex workflows cause token usage, latency, or quality evaluation drift, enabling you to optimize costs and improve response reliability.