03 / Enterprise AI

Models you own.

Some work can’t go to a public AI service: private data, regulated decisions, languages general models handle badly. We deploy and train models that run in your environment.

VOICE · TEXTYOUR ENVIRONMENTEVALUATION · RERUN ANY TIMEBaselineAdapted

How we measure it

A baseline before, the same numbers after.

Every model is evaluated against a baseline before it ships. Later changes are scored on the same test set, so you’re comparing like with like.

  • 01Accuracy on your test set
  • 02Consistency across repeat runs
  • 03Latency
  • 04Cost per request

How it runs

Four steps, the same on every project.

  1. 01

    Map the work

    We sit with the people who do the work today and map the process as it actually runs.

  2. 02

    Measure the baseline

    Time, errors and cost for the task as it is now, written down before we build anything.

  3. 03

    Build in small releases

    Working software early, reviewed with you as it develops.

  4. 04

    Report the same numbers

    After launch we measure the same things again, so the result is a number, not an opinion.

Questions

What buyers usually ask.

  • That depends on what you need. Models can run on your own infrastructure or a private cloud, so data never leaves your environment. Where a hosted model fits better, we tell you exactly what it sees.