Catch model drift before your users do
“The model you evaluated in January is not the model serving traffic in June — and nothing in your stack will tell you.”
Continuous eval pipelines with drift alerts, A/B comparison across versions, and audit-grade promotion gates.
QuratorTech & SaaSBanking & Financial ServicesTelecom & MediaAI Product OwnerQE / Engineering Leader
How we approach it
01
Scheduled re-evaluation
Eval suites run on schedule and on every deployment.
02
Drift thresholds
Real-time alerts when quality metrics move.
03
Promotion gates
No model version promotes without passing its eval battery.
Measured outcomes
↓70%
Drift detection time
50+
Built-in eval metrics