Agent failures rarely look like simple errors. A run may complete successfully while a tool silently retries, a handoff stalls, cost spikes, or the final answer becomes less useful.
AnoSys gives teams a trace-level view of production AI behavior and connects each span to evals, cost, user impact, infrastructure, and business outcomes.
Trace each run as an execution record, then connect slow spans, tool failures, handoffs, retries, and model calls to evals, cost, releases, and user impact.
Record agent turns, prompts, completions, tool calls, handoffs, retries, latency, and token usage.
View the run in order so engineers can see which span or dependency changed behavior.
Connect the trace to eval failures, cost spikes, infrastructure events, and affected users.
Send the incident to the owning team with the span, evidence, and downstream impact attached.
Yes. AnoSys captures agent turns, handoffs, model calls, and tool calls so teams can understand the entire run, not just the final response.
No. AnoSys supports OpenAI, Claude Code, Anthropic, custom LLMs, OpenTelemetry, REST APIs, and SDK-based instrumentation.