AI Agent Observability

Once an AI agent moves past a demo and into production, a new failure mode shows up. It's slow, it's burning through tokens, and every so often it does something you didn't expect, but you can't tell which step actually caused it. We built AI Agent Observability to unify sessions, traces, spans, model calls, tool execution, token cost, and risk events in one place, so debugging an agent looks like debugging any other distributed system instead of detective work.