01 · AI Solutions
Model Support, Monitoring and Upgrade
A model is not finished at launch. Data shifts, needs change, and performance must be watched.
AI Solutions
Model Support, Monitoring and Upgrade
A model is not finished at launch. Data shifts, needs change, and performance must be watched.
Showing 1 of 5
- 1Monitor live
- 2Detect drift
- 3Collect feedback
- 4Retrain and re-test
- 5Upgrade or retire
What We Do for You
- Monitor live performance against real outcomes.
- Watch for drift and tell you when it appears.
- Capture user corrections into the next training set.
- Retrain on a cadence with the same test gate.
- Evaluate newer models side by side before switching.
How this is bought: Bought as a monthly managed service on a rolling term, with a written service schedule. Build an estimate for your case.
Our Approaches Explained
Performance monitoring
Tracking accuracy and quality against live outcomes, not just launch-day scores.
Data and concept drift detection
Noticing when the world the model learned no longer matches the world it serves.
Feedback capture
Recording corrections from users and routing them into the next training set.
Scheduled retraining
Refreshes on a cadence or on a drift trigger, with the same test gate as the first release.
Incident handling for AI
A defined response when the model produces harmful, wrong or leaking output.
Version upgrade path
Moving to a newer base model with side-by-side evaluation before switching.
Cost and usage review
Regular review of spend against value, with options to reduce.
Documentation and handover
Runbooks and training so your team can operate the system without ARRIX in the room.
The Standards We Work To
MLOps monitoring practiceDrift detection methodsNIST AI RMF govern functionService level objectives (SLOs)
We follow the structure and controls these standards describe. We do not claim to be certified against them - where you need a formal certificate, we prepare the evidence and an accredited body performs the audit.
What You Get
- Monitoring dashboard and alerts
- Drift and retraining policy
- Feedback loop design
- Upgrade evaluation report
- Support runbook and training
Models under active monitoring91%
Drift alerts configured87%
Retraining tested before switch100%
These are the areas clients most often ask us to improve. Your project sets its own targets, measured and agreed with you.