SUBSTRATE CLOUD
Europe’s AI Cloud - Built for Sovereignty and Scale
Run, scale, and secure every stage of the AI lifecycle from training to inference
inside the European jurisdiction, with global availability & reach.
Substrate Cloud delivers the performance of a hyperscaler with the compliance
of a sovereign operator.
Purpose-Built for AI
Every layer of Substrate Cloud is optimized for AI workloads and enterprise orchestration. Customers gain instant access to scalable compute, persistent storage, and managed Kubernetes environments all protected by Substrate governance.
Core capabilities
Compute
- AI-optimized compute powered by NVIDIA’s H100, H200, and next-generation Blackwell and Vera Rubin architectures.
- Bare-metal or virtual nodes.
- Elastic scaling via API or Kubernetes.
Storage
- NVMe + S3 hybrid with replication & snapshotting.
- Immutable (WORM) storage for compliance.
- Multi-region replication inside the EU.
Networking
- InfiniBand + GPUDirect for high-throughput.
- Private VPCs, VPN & direct interconnects.
- Edge delivery points across EU regions.
Security
- ENS High | ISO 27001 | GDPR | SOC 2 (in progress).
- AES-256, BYOK/HSM, TLS 1.3.
- DDoS + WAAP mitigation.
Regions & architecture
Substrate Cloud operates from sovereign facilities in Spain and across Europe, with extended availability in global regions for low-latency workloads.
All European regions are governed by Substrate under EU law, ensuring that data never leaves European jurisdiction. Customers can choose dedicated sovereign capacity or elastic regional compute for scalability.
Observability & governance
Transparent monitoring, real-time billing, and compliance dashboards keep you in control. 99.95% SLA availability with predictive alerts and automated incident response.
Hybrid & multi-cloud integration
Connect Substrate Cloud to existing on-prem or multi-cloud environments through private links and federated identity. Maintain data residency while extending compute capacity globally.
Ideal for
- LLM training and fine-tuning
- Inference and serving at scale
- RAG and agent workloads
- Data-sovereign MLOps pipelines
- Federated research and public-sector AI
