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what we do
Evals & Monitoring
Know whether your agents are working — before your customers tell you they aren't.
The problem
Agents fail quietly. A model update, a changed API response, or a new edge case degrades quality without throwing an error. If you're not measuring, you hear about it from a complaint.
“Looks good in the demo” is not a quality bar. You need repeatable evals and live monitoring tied to the outcomes you care about.
What we build
- An eval suite: representative cases, graded automatically, run in CI and before every release.
- Regression detection when a model or dependency changes.
- Distributed tracing across the agent graph and its tool calls.
- Cost and quality dashboards — per run, per workflow, per day.
- Alerts on quality drops, cost spikes, and error-rate changes.
How it works
- Collect real cases and define what a good outcome looks like for each.
- Build graders — exact, rubric, or model-graded — for those cases.
- Wire the suite into CI and a pre-release gate.
- Instrument the running system and put dashboards where your team already looks.
What you get
- Eval suite and grader library in your repo.
- CI integration and release gate.
- Tracing and dashboards, with alert routing.
Run it your way
Every build ships one of two ways. Most engagements start managed and move in-house once the team is ready — some stay managed for good.
how we build
- The eval harness runs against any runtime; graders are version-controlled with your code.
- OpenTelemetry tracing; dashboards in Grafana, CloudWatch, or your existing stack.
- Model routing, so you can test a cheaper or newer model against the suite before switching.