Language models trained and run entirely inside your own environment. Queries cross the boundary inward. Your data does not cross outward.
Every hosted provider's privacy story ends with a promise. This one ends with a network boundary: the training data and the inference both happen on your hardware, in your private cloud, or inside an air-gapped network that cannot reach an external API at all. It is a structurally different claim, and it is the only one that survives an air-gap requirement.
Illustration of the architecture. Nothing on this diagram ever crosses outward, because nothing does in the product either.
The prompt, the documents and the fine-tuning corpus all leave your network to reach the model. Retention policy, region choice and contractual promises all sit on the far side of that crossing — and an air-gapped network cannot make it at all.
The weights and the runtime come to you. Training and inference happen inside your perimeter, so there is no crossing to govern, no region to choose, and nothing on the far side to trust.
Organisations that usually reach this page are operating under one of these:
Healthcare, protected health information.
Financial institutions and recordkeeping.
Law firms, attorney–client material.
Government and defence workloads.
These describe the rules our customers work under. SovereignLLM does not hold a certification of its own — see below.
Pre-launch. This is the intended shape, stated as design rather than as a shipped feature list.
Your own hardware, your private cloud, or a fully air-gapped network with no outbound route.
Domain-specific models trained on proprietary material that never leaves the boundary to be trained on.
Your object store, or an encrypted managed one — with the option to train and serve without us touching the data at all.
REST and SDK access for existing workflows, with logging suitable for internal compliance reporting.
Indicative, not a quote — the shape of the work varies too much for a price list to be honest. Scope comes out of the first conversation.
We bring the models, you bring the hardware.
Custom models on your own corpus.
No outbound route at all.
Leave an address and we will start with what you are actually allowed to deploy, what hardware you have, and whether this is even the right shape for you.
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