Sovereign AI has become viable.

Three years ago, running high-quality AI meant a foreign cloud and a bill in dollars. Public institutions and banks across the region had to choose between forgoing AI altogether and compromising their own data-residency rules. That dilemma has dissolved faster than anyone predicted: inference on commodity hardware, in-region or on-premises, is now economically reasonable.

It is not only a matter of cost. It is a matter of boundaries: where the model stops, where your documents begin, and who can see what. An intelligence that answers from your documents, within your scope, sending nothing to a third party for training, is not a second-best compromise — it is the only configuration compatible with public governance data or supervised banking data.

The trade-off is discipline: the intelligence must cite its sources, state its confidence level, and stay silent when the data is missing. That is what we call “grounded or silent”. Sovereignty is not only the location of the server; it is the refusal of the plausible answer.

We build for that world: on-premises, in-region or in a verified cloud, under one contract, with the same guarantees. The hosting choice belongs to the institution; traceability is not negotiable.