Model-Agnostic
Sovereign AI
The model is a component, not a commitment. Serve open-weight models inside your own perimeter, bring in frontier models where policy allows — and swap either without rebuilding a thing.
What is sovereign AI?
The model you pick today will not be the best one in a year, and the supplier you pick may not be one you still want. This is about running AI so that changing the model is a configuration change rather than a rebuild — and so your data never leaves ground you control.
Read this if you're wary of being locked into one AI supplier, or required to keep data inside your own perimeter.
Sovereign AI is model-agnostic AI run entirely inside your own perimeter — not tied to any single model or vendor. The AI OS serves open-weight models with vLLM in fully air-gapped, on-premises environments, and can also integrate frontier commercial models where policy allows. You can switch between models without re-architecting, and your data, models, and choices stay under your control.
Tying your organisation to one model or one vendor is a strategic risk: prices change, terms change, and capability moves quickly. Sovereign AI removes that dependency. The AI OS abstracts the model from your processes, so you can run open-weight models on your own hardware, bring in a frontier model where it is permitted, and change your mind later — all without your data ever leaving your perimeter.
Model-Agnostic
The AI OS is not tied to any single model or vendor — run open-weight or frontier models behind the same governed processes.
Open-Weight via vLLM
Serve open-weight models on your own hardware with vLLM, a high-throughput inference engine, fully air-gapped and on-premises.
Switch Models Freely
Swap the model behind a workflow when a better or cheaper option appears — no re-architecting, because the model is abstracted from the process.
Sovereign AI in the Scrydon platform
One integrated, sovereign architecture. Here is where Sovereign AI sits — highlighted against the full stack it works with.
The AI OS for Humans & AI Agents
Ontology & Semantic Layer, one connected model for your data, knowledge & processes
Combining the best of data lakes, data warehouses and search
Governed access to every model, and the agents & workflows that execute across your systems
Integrate across A2A, MCP, legacy systems and data sources
Secure domain federation, trusted data sharing, and cross-boundary intelligence
Sovereign Foundations
Sovereign AI in depth
Human + AI Orchestration
The AI OS for Humans & AI Agents
The Human + AI Orchestrator is the operational runtime at the heart of the AI OS — also called the Agentic OS — scheduling, routing, and governing every task across your enterprise, whether executed by an AI agent, an existing system, or a human.
Most organisations have broken processes: encoded in siloed systems or locked in people's heads. The AI OS makes them visible and executable. It captures intent, synthesises context, acts — then feeds every result back into the ontology so the next run is smarter. All of it inside your perimeter.
The AI Runtime is where AI actually executes: the AI Gateway that governs every model call, and the agentic AI workflows that turn those calls into work done across your systems. One is the way in, the other is what happens next — and both run under the same identity, policy and audit chain.
Two halves, one control plane:
- Gateway — one governed route to every model: Existing applications and coding agents point at a single endpoint instead of a vendor. Any model behind it, the vendor key never issued to a developer, and every call attributed to a person, capped and audited.
- Workflows — agentic AI that executes: Orchestrated workflows safely link frontier models, internal tools and enterprise memory, combining the reasoning of frontier AI with strict, deterministic steps so business-critical processes stay predictable.
- Autonomous execution within boundaries: Agents act autonomously inside defined limits, retrieving context from your data lakehouse and acting through approved tools — with a human in the loop wherever your policy says so.
Deployed securely inside your own infrastructure, the runtime draws on your cognitive enterprise to act decisively. Whichever half a call starts in, it resolves the same credential, meets the same policy and lands in the same audit trail — so adding governed agents later never means standing up a second control plane.
“Sovereign” is not a label on a datasheet
It is five tests you can run against a live system. Score any vendor on jurisdiction, keys, operating staff, disconnected mode and exit — plus whether the offer covers all four layers, and whether each answer was demonstrated or asserted. Twelve questions, nothing leaves your browser.
Score a vendor- Jurisdiction
- Keys
- Operating staff
- Disconnected mode
- Exit
- Four layers
Run it once per name on the shortlist — including the incumbent, and including us.
Any model, inside your perimeter
The AI OS treats the model as a replaceable component, not a foundation. It abstracts the model away from your business processes, so the same workflows, context, and governance apply whichever model is doing the reasoning — and the model can change without anything else changing. For the tools that call models directly — coding agents, applications — the same holds through the AI Gateway: one governed endpoint they point at instead of a vendor, behind which a frontier API today becomes an open-weight model on your own hardware tomorrow by configuration, never by re-architecture.
Open-weight on your hardware — Run open-weight models entirely on infrastructure you control, with no external API dependency.
vLLM serving — Serve those models with vLLM — an open-source, high-throughput inference engine — on-premises or fully air-gapped.
Frontier models where allowed — Integrate frontier commercial models where policy permits, with data kept inside your perimeter.
Switch without re-architecting — Change the model behind a workflow at any time; the AI OS abstracts the model from the process, so nothing else has to change.
No lock-in, no data leaving your perimeter
Depending on a single model or vendor concentrates risk in something you do not control — pricing, availability, terms, and roadmap can all move against you, and your most sensitive data ends up flowing to a third party. Sovereign AI keeps the leverage with you: models run inside your perimeter — on your own hardware or fully air-gapped — you choose the best one for each task, and you can replace it tomorrow without re-architecting. Your data, your models, and your choices stay yours.
Frequently asked questions
What is sovereign AI?+
Can it run open-weight models on-premises or air-gapped?+
Can we switch between models?+
Does it support frontier and commercial models too?+
Does our data leave our perimeter?+
Explore the platform
Prefer to write? Email hello [at] scrydon.com and we will get back to you.
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