AI evaluation and guardrail harness.
A repeatable test system for an AI product or agent: representative cases, expected behaviour, quality measures, permission tests, cost and latency tracking, and a review queue for failures. Changes can be measured before they reach users instead of judged from a handful of demos.
Product and technology teams moving an AI prototype toward production, or operating a system whose quality is currently assessed by anecdote.
Scoped after discovery
3–6 weeks
Commercial terms follow the diagnostic, so the number reflects the actual system rather than a generic package. Commitments stay staged; you never take the whole project on faith.
What building it involves.
- 01
Representative evaluation dataset
- 02
Task-specific quality and safety measures
- 03
Tool, permission, and refusal tests
- 04
Regression runs for model and prompt changes
- 05
Cost, latency, and failure reporting
- 06
Review workflow for ambiguous cases
Tell us about yours.
Every build starts with a short conversation and a scoped, fixed-price first stage.