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A precision laboratory balance with a calibration weight resting on its pan.

AI Evaluation

Know it is better before it ships

A prompt change looks better in a demo. Your scored suite says if it is.

Book a readiness reviewAI Test Automation
  • A fixed dataset drawn from your own traffic
  • A scoring method you agree before the first run
  • A baseline you measure each change against
  • A release gate that holds when the score drops

Example record

See the score before you ship

So you see which cases a change breaks, against the release running today.

The gate names the cases that failed.

eval · candidate against baselineSample log

  • Cases from support tickets

    answers signed off by a domain expert

    Pass

  • Policy questions

    rubric, named reviewer

    Pass

  • Refund edge cases

    score below the agreed threshold

    Blocked

  • New document type

    no cases written yet

    Add cases

How a model gets worse quietly

Nobody ships a regression on purpose. It arrives with a prompt edit, a model upgrade or a new document type.

  • A spot check reads a handful of answers

  • A provider upgrade changes behaviour under the same prompt

  • A fix for one case breaks cases nobody reread

  • Your users notice before your team does

Capabilities

What your suite is made of

Your domain team helps build it once. It runs on each change after that.

01Cases from your own trafficQuestions your users asked, with answers a domain expert signed off. Synthetic cases fill the gaps.
02A scoring method you can defendExact match where the answer is fixed. A rubric with a named reviewer where it is not.
03A baseline per releaseThe score of what runs today, stored with the code. A change has a number to beat.
04A gate in the pipelineA drop below the threshold blocks the release. You get the names of the cases that failed.

Model

What we fix, and what you decide

What we fix

  1. F1A dataset, a scoring method and a baseline before tuning starts
  2. F2A threshold you agree in writing
  3. F3Failed cases reported by name, with the diff

What you decide

  1. C1Model and provider
  2. C2Where the threshold sits
  3. C3Who signs off a rubric case

Related

Where to go next

Next step

Send us the questions your users ask.

What you get: a first suite and today’s score, a number to hold the next release to.

Book a readiness review →