Sovereign AI

What is Sovereign AI?

Sovereign AI is where an organization is capable of building and operating their own AI systems, ensuring data security and compliance with local regulations within the organization’s boundaries. Sovereign AI is often associated with nation states as the organization, implying self-sufficiency and control over a nation’s over AI infrastructure, policies, and data usage.

Sovereign AI is often a pseudonym for air-gapped environments, where AI systems are deployed and managed in highly secure, isolated environments that are physically or logically disconnected from the Internet. The essence of data sovereignty is security and compliance with national and organizational regulations by preventing unauthorized data access. Sovereign AI systems help organisations keep their data secure while being able to govern, manage and control their own data.

Sovereign AI does not require the pre-training of foundational large-language models (LLMs), which are now widely available (and commoditized) as both commercial and open-source offerings. Organizations can use trusted LLMs, trained at external organizations, to operate sovereign AI systems.

Why is Sovereign AI Important?

Sovereign AI is essential in industries and sectors where data is sensitive and needs to be managed securely. For example, Sovereign AI is critical in public and financial services where large volumes of personal or infrastructure data are managed and where fraud or security breaches are a real threat. In these environments Sovereign AI systems must be able to operate independently and have full control over data and AI workflows to meet regulatory and operational requirements.

Sovereign AI with Hopsworks

Hopsworks is a modular, scalable AI Lakehouse platform designed to address the challenges of air-gapped environments. As a platform Hopsworks provides AI sovereignty through:

• Air-Gapped Deployments: Hopsworks can be deployed in fully isolated environments with no external network dependencies, security and data sovereignty.
• Built-In Data Governance: Data lineage, versioning and governance features to meet strict regulatory requirements.
• GPU and Compute Management: On-premises GPU clusters for scalable model training with Ray and deployment in resource heavy scenarios.
• Enterprise-grade model serving at scale with KServe/vLLM, including on GPU clusters.
• Real-Time Feature Serving: Feature Store for real-time feature serving in isolated environments for AI driven decision making.
• Scalable data processing with Spark, Pandas/Polars/DuckDB, Flink, Feldera, and more.

By providing an end-to-end AI platform in air-gapped environments Hopsworks enables organisations in defence, government and critical infrastructure to build and operate AI systems while keeping full control over their data and operations.