Reliability is measured, not assumed.
The operational layer that keeps production AI dependable: live evaluation, alerting, and guardrails.
- 24/7 monitored operation
- < 5 min drift-to-alert (illustrative)
- 99% uptime on deployed systems
What ships.
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Evaluation on live traffic
Accuracy, groundedness, latency, and cost scored continuously on real usage, not a frozen test set.
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Drift and regression alerting
Quality changes surface to your on-call before users feel them, with the failing traces attached.
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Guardrails that make change safe
Policy checks, canary rollouts, and rollback paths so shipping improvements never risks the baseline.
How it shows up day to day.
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Runbooks your team owns
Every alert has a documented response; every response is rehearsed at handover.
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Dashboards operators read
Quality and cost in the language of the workflow, not of the model.
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Quarterly capability reviews
A standing rhythm that turns incidents into roadmap, together.