Observability & Evals
Production observability for AI systems: traces, metrics, evaluation harnesses, drift detection, and continuous improvement loops.
What it is
Observability for AI is more than logging and dashboards. It includes evaluation harnesses that run on every deployment, drift detection on retrieval and generation, user-feedback loops, and the continuous-improvement workflow that keeps a system better six months in than at launch.
What we deliver
- Prompt and response tracing with full context for every interaction
- Per-feature evaluation datasets and continuous eval pipelines
- Drift detection on retrieval, generation, and downstream outcomes
- User feedback capture (thumbs, structured ratings, escalation flags)
- Cost and latency dashboards per tenant and per workflow
- Quarterly model and capability review reports
Why this matters
Production AI is not a "ship and forget" system. The customers we serve longest are the ones whose systems get measurably better over time — and that requires the observability and eval foundation to be there from day one.
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Ready to ship this inside your environment?
Bring your use case to a 30-minute discovery call. We'll tell you whether this technology fits and how it gets deployed.