Enterprise AI / Private deployment

AI that never leaves your building.

For data that can’t go to a public AI service: open-weight models running on your own servers or private cloud, sized to your volume and tested before go-live.

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What we build

Where we usually start.

On your servers

Models served on your own hardware, next to the data they need.

Private cloud

A dedicated environment in your cloud account, with nothing shared.

Sized to your volume

Hardware and model chosen for your real request volume, so it’s fast enough without paying for idle machines.

Secured and monitored

Access control, logging and monitoring, so you know who asked what and how it performed.

How we measure it

A baseline before, the same numbers after.

Before go-live we load-test the system and score the model on your own cases. After launch we keep reporting the same numbers.

  • 01Accuracy on your test set
  • 02Response time under load
  • 03Uptime
  • 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.