AI evaluation
Hallucination and bias testing
Grounding and fairness are measured, not asserted. Thresholds are agreed with your governance function, wired into release gates, and reported together with the method — so every number survives audit review.
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
How do you measure hallucination?
Grounding and faithfulness checks against source material, plus domain-specific factuality suites with agreed thresholds.
Can bias be measured objectively?
Bias is measured across defined cohorts with documented methods. We report the measurement and the method — both are auditable.
What happens when a model fails a threshold?
The release gate fails. The report shows which inputs failed and why, so the fix targets causes rather than symptoms.