Why LLM Research in Europe Is Moving to Sovereign Cloud Infrastructure

Europe is building its AI future but where it builds matters.

From multilingual healthcare assistants to defence-grade document analysis, Europe is accelerating its investment in large language model (LLM) research. These models need massive computing power, continuous access to high-quality data and full regulatory compliance. And the most important yet overlooked aspect of compliance is now defining where and how European AI is built.

Cloud services used to be a simple question of speed and scale. Now, European researchers must ask:

• Is this infrastructure GDPR-compliant?

• Can it protect our IP?

• Will it comply with EU AI Act obligations?

Continue reading as we discuss why LLM Research in Europe is moving to Sovereign Cloud Infrastructure in 2025.

Why Sovereign AI Infrastructure Matters for LLM Research

Sovereign AI infrastructure refers to cloud environments that are physically and legally rooted in national or EU jurisdictions. Unlike general-purpose cloud services, these infrastructures are built to meet regional compliance, data residency and sovereignty requirements (which is EU in this case).

• Data Residency within the EU or National Borders: All data including training, inference, metadata and logs must remain physically and logically located in EU territories. This ensures compliance with data transfer laws and eliminates exposure to foreign surveillance mandates.

• Jurisdictional Control: Providers must be legally domiciled in the EU and not subject to extraterritorial laws like the U.S. CLOUD Act, which allows U.S.-based firms to share data with American authorities, even when hosted abroad.

• Certification for Public Sector Use: Certain cloud providers are certified under legal frameworks for data security. For example, SecNumCloud in France mandates that customer and technical data must be hosted and processed within France or the EU, with protections against extraterritorial access. Or C5 in Germany, a certification required for cloud security for cloud providers serving the German government and public-sector contractors.

For LLM researchers in Europe, this ensures:

• Full control over data compliance

• Protection of research IP and training datasets

• Alignment with GDPR and the EU AI Act

When LLM Researchers Need Sovereign Infrastructure

Any organisation or individual conducting LLM research in Europe will need a Sovereign AI Infrastructure when:

Training Large-Scale Foundation Models

Training LLMs at scale requires vast GPU clusters for AI, petabytes of data and continuous access to high-throughput storage and networking. These operations can raise several compliance flags, like:

• Data Jurisdiction: If training occurs on a U.S.-controlled hyperscaler, even when hosted in the EU, there is legal ambiguity about who has ultimate access.

• GDPR Compliance: Articles 44 of the GDPR place strict restrictions on international data transfers outside of the EU/EEA. Using a non-sovereign provider, even with standard contractual clauses or Binding Corporate Rules, introduces compliance risk.

• Sensitive Data Handling: When AI model training involves personal or identifiable data, even anonymised, full legal and physical control over data residency is critical.

Working with Sensitive or Regulated Data

Foundational models are being applied to domains with high legal sensitivity across regulated areas such as:

• Healthcare: Training on patient records or clinical data must adhere to GDPR, national health privacy laws and specific cross-border data transfer restrictions.

• Finance: Transactional and behavioural data used for fraud detection or financial forecasting is often regulated by EU-level and national financial authorities.

• Defence and National Security: Models trained on classified or restricted datasets require absolute isolation from foreign jurisdictions.

National AI Labs and Government-Supported Research

European nations are launching numerous national AI initiatives and these efforts aim to ensure:

• Technological Autonomy: Reducing dependence on foreign platforms.

• Legal Compliance: Meeting country-specific mandates for data handling and research ethics.

For such initiatives, sovereign infrastructure is a prerequisite. Without it, national strategies for AI leadership would be undermined by legal and operational dependencies on non-EU platforms.

Enterprise and Government Collaboration with Border Restrictions

Yes, public-private partnerships are imperative for scaling AI research and deployment. However, they come with strict data residency requirements:

• Eligibility for Contracts: Many government RFPs mandate that service providers maintain full data sovereignty.

• Cross-Border Limitations: Enterprises working across multiple EU countries still prefer infrastructure that guarantees unified compliance.

How EU Laws Reinforce This Need

Let’s read how EU laws add to the needs of LLM workloads, being compliant and sovereign:

GDPR (Articles 44–49)

The GDPR restricts how personal data can be transferred outside the EU. These provisions become especially critical when applied to AI training:

• Data Transfers: Any transfer of personal data to non-EU countries must meet adequacy, Standard data protection clauses (SCCs), Binding corporate rules (BCRs) or explicit consent requirements, according to Article 46 GDPR.

• Hefty Penalty: Transfers of personal data to a recipient in a third country or an international organisation could result in hefty penalties under GDPR. Fines can be up to 20 million euros or, in the case of an undertaking, you may end up to 4 % of your total global turnover of the preceding fiscal year, whichever is higher (according to Article 83(5) GDPR). 

Using sovereign infrastructure which adheres to GDPR eliminates the ambiguity of cross-border processing, ensuring that all personal and sensitive data remains fully within EU jurisdiction.

EU AI Act (Section 3: Obligations of Providers and Deployers of High-Risk AI Systems and Other Parties)

Some of the major obligations of Section 3 of the EU AI Act for providers and deployers of high-risk AI systems include:

• Compliance and Conformity: Providers must ensure their AI systems meet all requirements in the Act and undergo conformity assessments before being placed on the market in accordance with Article 47.

• Transparency and Documentation: Providers are required to maintain technical documentation, affix CE markings and issue an EU declaration of conformity to demonstrate compliance under Article 48.

• Log and Data Retention: Both providers and deployers must retain logs generated by high-risk AI systems deployers for at least six months (according to Article 19).

• Human Oversight: Deployers must assign qualified individuals to monitor AI systems and ensure they operate under proper human supervision according to Article 14.

Compliance is significantly streamlined when the infrastructure is under EU jurisdiction. Non-sovereign clouds introduce logistical and legal complications that make these requirements more difficult to fulfil.

Digital Sovereignty Mandates

Beyond GDPR and the AI Act, several national strategies explicitly promote digital sovereignty, such as Gaia-X, European governments and the European Union to strengthen the European cloud market while responding to data privacy and cybersecurity concerns

What You Can Do

Ensure GDPR and EU AI Act Alignment with High-Performance Sovereign Infrastructure

If you are engaged in deploying LLM workloads within Europe, you must align your workflows with European legal requirements without trading performance for compliance. Modern sovereign cloud providers are surpassing their hyperscaler counterparts by offering high-performance Sovereign Infrastructure:

• Full jurisdictional compliance with GDPR, the EU AI Act and national mandates

• High-performance infrastructure featuring powerful GPU clusters such as NVIDIA HGX H100, NVIDIA HGX H200 and the upcoming NVIDIA Blackwell GB200 NVL72 with advanced networking like NVIDIA Quantum InfiniBand and high-speed data storage using NVIDIA-certified WEKA with GPUDirect Storage for ultra-low latency in data-intensive workloads.

NexGen Cloud offers sovereign cloud deployments with support for high-intensity AI workloads including large-scale LLM training, Inference and more. NexGen Cloud enables you to build a compliant AI infrastructure without compromise.

FAQs

What is the EU AI Act?

The EU AI Act is Europe’s regulatory framework governing the development and use of AI systems, focusing on safety, transparency and accountability.

What is GDPR?

The General Data Protection Regulation (GDPR) is the EU’s data privacy law, regulating personal data use, storage, processing, and cross-border transfers.

Why is data sovereignty important for AI?

Data sovereignty ensures sensitive data remains under national or EU control, reducing legal risks and enabling regulatory compliance during AI development.

What is sovereign AI infrastructure?

Sovereign AI infrastructure is cloud infrastructure physically and legally located in the EU, free from foreign legal control.

Why cannot European researchers use U.S.-based cloud providers?

Using U.S.-controlled cloud providers risks non-compliance with GDPR due to potential foreign access via laws like the U.S. CLOUD Act.

Does sovereign infrastructure compromise performance?

No. Cloud providers such as NexGen Cloud offer sovereign AI cloud deployment options while offering high-performance infrastructure including cutting-egde GPUs, InfiniBand networking and high-throughput storage.