Private AI
AI dedicated to your privacy requirements.
When the data involved calls for a tighter boundary, inference can run in an environment reserved for you rather than on a shared service.
The right question is not "where is the data"
An application can be hosted in one country and call a model running elsewhere. What matters is not only where data rests, but where processing runs and what travels with each call.
A private AI option answers that question: inference runs within a dedicated boundary, on capacity allocated to you, and what leaves it is determined by your configuration.
This has a cost and trade-offs. Dedicated capacity has to be sized, operated and paid for, whereas a shared service absorbs load variation.
What an assessment decides
The execution boundary
Where inference runs, which components stay shared, and what crosses the boundary at each call.
The model choice
A self-hostable model does not have the same capabilities as a managed service. The choice follows your real tasks, not a generic leaderboard.
Sizing
Required capacity depends on your volume and expected response times. It is measured, not guessed.
External sources
A web search or monitoring leaves the boundary by definition. What is allowed and what is sent are defined explicitly.
This option is subject to a dedicated assessment. We display no price and no standard configuration: they depend on your volume, your tasks and the model chosen.
Questions worth preparing
Does this guarantee compliance?
No, and nobody should claim it does. A controlled execution boundary is one element of a compliance case, not a certification. That case depends on your processing purpose and responsibilities.
Is performance equivalent?
Not necessarily. A smaller dedicated model may suit your tasks perfectly well, or not. The assessment and pilot establish that on your real cases.
Can we start on managed cloud and switch later?
That is a common path: validate usage first, tighten the boundary afterwards. The move requires fresh qualification; it is not transparent.