As AI agents become part of day-to-day enterprise operations, teams often struggle to understand how those agents behave once they are live. Workflows span multiple models, tools, and systems, and even simple interactions can involve many steps behind the scenes. Without clear visibility, it becomes difficult to explain outcomes, diagnose failures, or prove that agents are operating reliably and within guardrails.
AI Observability brings clarity to this complexity. Built into the Agent Platform, AI observability helps teams monitor AI agent performance in real time. With AI agent observability and agent performance monitoring, teams can track success and failure rates, response times, and workflow outcomes, giving them confidence in how agents perform across production environments.
Behind the scenes, the AI observability platform provides detailed agent tracing and analytics. Every action an agent takes is captured, including tools used, models selected, latency, and token usage. Monitoring events record system changes, user actions, and configuration updates, while real-time dashboards surface issues early and support faster debugging when human review is needed.
The result is stronger trust and operational control. Teams reduce risk, resolve issues faster, and scale AI agents with confidence, knowing performance, compliance, and reliability are continuously visible and measurable.