AI Quality and Evaluation

Measure how often your AI feature is wrong in production, and stop regressions before release.

Request a scoping call
Timeline
2-4 weeks
Engagement
Fixed-scope build
Practice
Assure

The situation

The feature performs well in demonstrations. No one can state its error rate in production, or whether the last prompt or model change improved it.

What we deliver

  1. [01] Evaluation set built from your real tasks
  2. [02] LLM judge calibrated against human labels
  3. [03] Regression suite that runs in CI on every change
  4. [04] Quality dashboard your product team can read

Controls you keep

  • Evaluation gate in CI
  • Versioned test set
  • Documented scoring method
  • Dashboard owned by your team

How it runs

  1. Week 1

    Baseline and task sampling

  2. Week 2

    Judge calibration

  3. Week 3

    CI integration

  4. Week 4

    Handover and training

Evidence

Start here

Have a problem AI might solve?

Describe the outcome you need. Within two working days you receive a written view on whether AI is the right tool, the risks to manage, and a proposed first step.

Request a scoping call [email protected]