AI Performance Monitoring
Release testing, compliance checks, live monitoring, and a scorecard that keeps production AI working and shows what it returns.
What we run
Release Testing
Score every release against test sets built from real cases, so accuracy and relevance are checked before an agent reaches users.
Compliance & Safety Checks
Run safety, data protection and policy checks on every release. A failed critical check blocks it.
Live Monitoring & Alerts
Track quality, speed, cost and rule violations in production, alert the team when they drift, and route flagged outputs to human review.
Cost & ROI Scorecard
Report productivity, quality, cost and compliance against the baseline set before launch, in numbers finance can check.
How it works
Instrument the AI output
Add logging hooks at every point where the AI produces a response so no output goes unobserved in production.
Test against real cases
Build test sets from real cases, then score each release with rule-based, model-based, and statistical evaluators for a multi-signal quality view.
Add compliance and safety gates
Turn policy, data protection and EU AI Act requirements into critical checks that stop a failing release from shipping.
Report to the business
Aggregate results into a scorecard and alerts wired to your team's existing channels, so engineering and finance read the same numbers.
Case study
AI support bot monitoring
Client case study coming soon. Details under NDA.
Applied in
Ready to put your AI systems under observation?
Let's design an evaluation and monitoring layer for your production AI.