Rivac LabsModel Monitoring & Drift Detection
Models don't usually fail loudly — input distributions shift, an upstream data pipeline changes its schema, or real-world behavior drifts from what the training data assumed, and the model just gets quietly worse for weeks before anyone with a dashboard notices. This service builds continuous monitoring for deployed models: tracking input and prediction drift, comparing outputs against ground truth where it's available, and alerting on decay before it shows up in the business metrics downstream. It's for teams running models in production with visibility that stops at uptime and latency. The result is a monitoring layer that flags a degrading model weeks before a customer complaint or a bad automated decision does.
How We’d Approach This
A clear, staged plan — not a black box
- 1
Diagnose current model outputs and available ground-truth signals to define what drift and decay look like for this model.
- 2
Pilot drift and performance monitoring on the highest-impact model to validate thresholds against real production traffic.
- 3
Review alert thresholds and escalation paths with the team so alerts route to the right owner without becoming noise.
- 4
Roll out monitoring and alerting across all production models, feeding into the existing on-call process.
What You Get
Deliverables from this engagement
- Drift and performance monitoring dashboards per model
- Alerting configured on data drift, prediction drift, and accuracy decay
- Documented baseline metrics and thresholds per model
- Runbook for triaging and responding to drift alerts
Six Ways We Could Architect This
Different engagement, different build — pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start — scoped small enough to prove itself before you commit to anything bigger.
Talk to us about Model Monitoring & Drift Detection