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Accelerator
Sovereign AI
Sovereign AI Platform Proof of Value
From validated use case to a running AI application on European infrastructure in nine weeks — including the governance, guardrails and evidence your compliance function expects.
Duration
9 weeks
Usual next step
AI Gateway Blueprint
The problem
Most enterprise AI pilots stall in one of two places. Either they never leave the demo, because nobody built the platform underneath them, or they cannot be deployed, because the data cannot legally or contractually go where the model lives.
The second problem is the one European enterprises keep hitting. The use case is sound, the value is real, and the moment it goes to compliance it stops, because there is no answer to where the data goes, who can see it, how the decision is logged, and what the EU AI Act obligations are for this system.
What we build
A working AI application on a platform foundation you can keep, running on European infrastructure, with governance built in rather than added afterwards.
The AI application itself: retrieval-augmented generation, an agent workflow, or a classification or extraction pipeline, built against your real data and your real use case
A model serving and inference layer on your sovereign target: European model providers, open-weight models you host yourself, or a sovereign offering of a major provider, chosen against your data classification rather than a preference
Data pipeline and retrieval layer, with the access controls of your source systems preserved rather than flattened
Guardrails: input and output filtering, prompt injection defenses, PII handling, and human-in-the-loop where the risk classification calls for it
Evaluation harness: a repeatable way to measure whether the system is getting better or worse, which is the thing most pilots skip and then cannot argue about
Full observability and audit trail: every request, retrieval, and model interaction traceable
EU AI Act positioning: risk classification for the system, the obligations that follow, and the technical documentation started rather than deferred
A platform foundation that the second and third use cases can reuse
Why “proof of value” rather than “proof of concept”
A proof of concept proves the technology works, which is rarely in doubt. This proves the use case is worth industrializing: measured against your data, with a cost model, an evaluation baseline, and a compliance position. At the end you have evidence for a go or no-go decision, and if the answer is go, the foundation is already there.
How it runs
Weeks | Phase |
|---|---|
1 to 2 | Use case validation, data assessment, risk classification, architecture and target selection |
3 to 6 | Build: platform foundation, data and retrieval layer, application, guardrails |
7 | Evaluation: baseline measurement, tuning, cost modeling |
8 | Hardening, security review, compliance documentation |
9 | Business review, industrialization roadmap, handover |
Who it is for
Organizations in regulated sectors with a validated AI use case that cannot be deployed on non-European infrastructure, and organizations that want the second and third use case to be cheap because the first one built the platform.
What happens next
If the value is proven, the path is industrialization: production hardening, the platform layer that serves multiple use cases, and an AI Gateway Blueprint where model access needs central control across teams.
Interested?
Tell us your starting point and the decision in front of you. We will come back with scope, pricing, and an honest assessment of whether this proof of value is right for you.