AI evaluation
Model monitoring
Drift and regression caught in hours, not quarters. Dashboards and alerting live in your stack and are owned by your team, with incident playbooks written before the first incident.
Discuss your AI initiativeScope of work
Process
How an engagement runs
01
Scope
We agree what to test, against which benchmarks and thresholds.
02
Harness
A reproducible test or evaluation harness is built in your repositories.
03
Execute
Suites run on every release; failures are triaged with your team.
04
Report
Findings, evidence and a remediation backlog, written for review.
Questions
Common questions
What is model monitoring?
Drift detection on inputs and outputs, plus regression evaluation on every model update, with alerting your team owns.
How fast is drift detected?
Within hours of onset for monitored signals. Dashboards and alerts are wired into your stack, not ours.
What is in an incident playbook?
Detection thresholds, rollback criteria and communication steps — written before the incident, not during it.