As AI adoption accelerates across Europe, organizations face a strategic crossroads:
Migrate everything to foreign hyperscalers for raw power, or do nothing to preserve sovereignty? Neither path is sustainable.

 

Between full-scale outsourcing and technological stagnation, a third option emerges — one that protects European interests without compromising on performance, flexibility, or scale.

 

The false binary: hyperscaler or nothing

Dominant cloud platforms promise scalability and speed, but they also introduce serious risks:

• Loss of control over sensitive data
• Exposure to non-EU legislation like the U.S. Cloud Act
• Dependence on opaque pricing and closed ecosystems

 

On the other hand, maintaining outdated or fragmented infrastructure internally stifles innovation and limits the ability to train and deploy modern AI models.

The choice shouldn’t be between compromise and inertia. It’s time for an alternative that aligns with European values, standards, and ambitions.

 

The third path: sovereign, scalable, and sustainable

This alternative is already operational — combining the sovereignty of local infrastructure with the computing power of hyperscalers, and the sustainability Europe demands.

 

Sovereign Infrastructure by Design

• Data centers located in France, operated under full European jurisdiction
• GDPR-compliant architecture with no exposure to extraterritorial legislation
• Full-stack control: from hardware to orchestration

 

Extreme Performance, Ready for AI at Scale

• 15,000+ GPUs available, including the latest NVIDIA H100, GB200, and A100
• Dedicated clusters, on-demand cloud, and inference-ready environments
• Instant deployment through API or intuitive interface

 

Radical Energy Efficiency

• PUE of 1.1 enabled by advanced Direct Liquid Cooling
• Up to 60% reduction in carbon emissions compared to traditional facilities
• Integration of waste heat recovery systems into local industrial and municipal networks

 

A real use case: from exploration to industrialization

A European deeptech company recently began training a generative video model. The journey looked like this:

1. Initial experimentation on on-demand GPU cloud, with no commitment or configuration needed.
2. Transition to a dedicated AI cluster, tailored for multi-node distributed training.
3. Scaling to production using orchestration tools and MLOps pipelines integrated with the infrastructure.

 

The outcome:

• 8× improvement in training throughput
• 35% reduction in compute costs
• Full sovereignty over data and environment

The model went from proof of concept to full production in weeks — not months — with no dependency on foreign providers.

 

Not just infrastructure, the foundation of AI sovereignty

This isn’t about selling GPUs.
It’s about building the backbone of European AI independence.

 

The mission is clear:

“Enable organizations — from startups and universities to public institutions — to access extreme compute power without sacrificing sovereignty, financial control, or environmental responsibility.”

 

This third path is not theoretical. It’s physical. It’s operational. It’s evolving.

 

The future is European, or it isn’t

Cloud and compute infrastructure must reflect the values and strategic goals of the ecosystems they serve. For Europe, this means:

• Trust over opacity
• Performance without compromise
• Innovation that scales sustainably

 

The future of AI cannot be built on blind dependencies.
It must be sovereign, responsible, and radically effective.

 

That future is already being deployed.