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focus area · sharing digital sovereignty

Shared Sovereignty

Full digital sovereignty — your own models, your own hardware, your own operation — is often too expensive for individual mid-sized companies. Complete dependence on a few hyperscalers is too risky. Shared Sovereignty is the path in between: companies share AI infrastructure but keep control over their data, their models and their rules.

The sovereignty dilemma of mid-sized companies

Operating AI models in your own data centre means investing in hardware, energy, specialist staff and ongoing model maintenance. For a single company with modest token volume that rarely pays off. The alternative — everything via external providers — raises questions about data protection, contract terms, price changes and dependence.

Both extremes can be calculated with the Sellium TCO model. Usually it shows: the economically and legally best point lies in the middle.

What Shared Sovereignty means

Several companies — along a supply chain, in a region or in an association — jointly use AI infrastructure in Europe: compute capacity, models, operation. Each company keeps separate data spaces, its own access rules and its own fine-tuning. Costs and operation are shared, not data.

Separate data spaces

Tenant separation at infrastructure, model and application level; no mixing of training or usage data.

Shared models

Open models, jointly operated and maintained; company-specific adaptations stay with the respective company.

European operation

Data centres and operators in the EU, clear contract terms, data processing under GDPR.

Exit capability

Data, configurations and adaptations remain portable — switching or bringing them back in-house remains possible.

Governance: who decides what

Shared infrastructure needs clear rules: who decides on model changes, updates and capacity expansions? How are costs distributed? How are security incidents handled? We shape this governance with the participants — as an operating agreement between the companies, with defined roles and escalation paths.

  • Steering committee of the participating companies with fixed decision rules
  • Transparent cost allocation by usage
  • Security and compliance standards (ISO 27001, TISAX) as the common basis
  • Documentation under the EU AI Act per company and use case

Who Shared Sovereignty is for

For companies that process sensitive data and still want to use AI productively; for supply chains in which several partners have similar requirements; for associations, clusters and regions that want to offer their members a common basis; and for companies that deliberately want to become more independent of individual providers.

What Sellium contributes

We plan the architecture, calculate the variants with the TCO model, shape the governance and accompany set-up and operation — vendor-neutral and with a view to the participants' concrete use cases. Where it makes sense, we work with European data centre and model partners.

privacy first ai

Sovereignty is not all-or-nothing

Control over data and models can be gained step by step. Shared Sovereignty makes the step affordable — without giving up the control that is decisive for your business.

Control

Your own data spaces, your own rules, your own adaptations — even on shared infrastructure.

Economics

Costs for hardware, energy and operation shared; calculated with the Sellium TCO model.

Independence

Open models, European partners, exit capability anchored in the contract.

process

How a shared AI infrastructure takes shape

From clarifying interests to joint operation.

  1. Step 1: Needs & partners

    Clarification of the participants' use cases, data types and security requirements; assessment of fit.

  2. Step 2: Architecture & TCO

    Target architecture with tenant separation, model selection, operating variants; cost comparison per company.

  3. Step 3: Governance & contracts

    Steering model, cost allocation, security standards, data processing and exit rules.

  4. Step 4: Set-up & operation

    Step-by-step set-up, onboarding of use cases, monitoring and continuous development.

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