Arth — Technology & Infrastructure
Sovereign at every layer.
Not just where the servers sit.
Data residency alone doesn't make a deployment sovereign. It has to hold at the compute layer, the model layer, and the application layer — together, not just one of the three. Arth is built to hold at all three.
The sovereign AI stack
Sovereignty has to hold at every layer
A private network connection doesn't make a deployment sovereign if the model or the compute underneath it isn't. All three layers have to hold.
Runs in your cloud, not someone else's
The application layer — matching, classification, generation — lives inside your own private cloud. You decide where the workflow runs and who can reach it, independent of where inference happens underneath it.
Owned, not rented
An open-weight model your team can run yourselves on dedicated GPU infrastructure, connected to your application over a private link — never a public endpoint. Not a proprietary model reachable only through someone else's API.
Dedicated, not shared
Isolated GPU infrastructure, hosted in a jurisdiction that satisfies data residency — and legal sovereignty, since who can be compelled to access it matters as much as where it physically sits.
Compute, ready now
Instant allocation of compute
Not a procurement cycle, and not a decision you have to make yourself. Every tier below is already vetted, dedicated, and ready — which one your workload needs is matched automatically, once Cob and Aria have done their part.
Example match — L40: 48GB · Inference-optimized
Arth — Model
Frontier LLM by default.
Sovereign model when it matters.
Most requests route straight to whichever frontier model your team already trusts — that's not a fight worth having, and not a choice you have to make. A specialized, self-hosted model exists for one job: the slice of work a frontier model was never going to be allowed to touch, regardless of how capable it is.
How Arth decides
One default. One exception.
Your team's preferred model handles almost everything. The sovereign model exists for exactly one reason — and Arth applies it automatically, not as a choice you make.
Your model, unless it can't be
Most requests go straight to the frontier LLM your team already trusts. No new tool to learn, no workflow to change — the routing is invisible until it needs to matter.
Automatic, not manual
Cob already knows which work is sovereignty-gated. Arth routes that specific slice to the specialized model on its own — nobody has to remember to flag it.
Still built for the job it does
The sovereign model is fine-tuned specifically for the gated work it handles — a narrower job, not a downgraded one, and open-weight by design, which is what makes it ownable in the first place.
How this fits together
Built by specialists. Delivered through Svarg.
Svarg doesn't operate GPU infrastructure or train domain-specific models ourselves — and we don't think we should. Arth is delivered in partnership with specialized compute and model providers who focus on exactly this problem, every day. Our role is to make sure the right capability shows up at the right point in your blueprint, integrated with the rest of your AI strategy — not to reinvent expertise that already exists.
If you're a compute infrastructure or specialized-model provider interested in partnering with Svarg, we'd like to hear from you.
Get in touch