Mfinite Kloud
MISSION 04

Trust & Evaluation

Tests that show what your AI system gets right, what it gets wrong and when that changes, written so your compliance team can follow them.

The problem

AI systems change under you: a new model version, an edited prompt, a new batch of documents. Without tests, the first sign of a regression is a customer complaint.

Public benchmarks don’t say much about your use. What matters is how the system handles your questions, your edge cases and your data.

What we build

  • Test sets built from real questions, with expected answers or sources, plus edge cases and deliberate attempts to break it.
  • Checks for accuracy, citation correctness, refusals, personal-data leaks, prompt injection and cost per answer.
  • An eval runner in CI that blocks a release when scores drop below agreed thresholds.
  • Production monitoring that samples live traffic, flags drift and turns new failures into new test cases.
  • Reports mapped to the NIST AI RMF or ISO/IEC 42001 when you need them. We don’t certify; your auditor does.

Reference architecture

Trust and Evaluation architectureTest sets of real questions and personal-data probes feed an eval runner in CI that runs on every model, prompt or data change. Scores for accuracy, refusals, leaks and cost decide whether a release goes ahead or is blocked with a report. Production monitoring watches for drift and feeds new failure cases back into the test sets.Test setsreal questions · PII probesEval runner in CIevery model, prompt or data changeScoresaccuracy · refusals · leaks · costReleasethresholds metBlockedreport says whyProduction monitoringdrift · new failure cases
A typical layout. The real one is shaped around what you already run.

What you own at the end

  • Test sets and the runner, in your repository
  • CI configuration and agreed thresholds
  • Report templates for engineering and compliance
  • A process for adding new failure cases

When it’s not the right fit

Works on new systems and on ones you already run. If nothing depends on the output yet, a short spot-check is enough for now.

Talk about Trust & Evaluation

Tell us roughly what you’re trying to build. A few sentences is plenty. We’ll reply by email.

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