What You Should Know
- The Danish Center for AI Innovation (DCAI) and clinical AI lab Corti have launched Corti Models, a governed, model-agnostic infrastructure layer providing European enterprises with sovereign control over AI deployments, data security, and compliance.
- The platform provides an OpenAI-compatible API supporting sovereign cloud and on-premises environments, allowing organizations to route workloads to leading foundation models without rewriting existing SDK integrations or prompts.
- Corti Models is powered by DCAI’s ISO-certified Gefion AI supercomputer (an NVIDIA-powered cluster), with DCAI investing in a scalable NVIDIA Blackwell B300-based cluster to serve as a national inference platform across Denmark and the Nordic region.
Mitigating Provider Dependency and Data Residency Risks
As enterprise workflows increasingly rely on frontier generative models, dependence on single-vendor foreign AI providers exposes organizations to unexpected service outages, unforecasted API price shifts, and data transfer risks under European regulations like GDPR, NIS2, DORA, and the EU AI Act.
Corti Models mitigates these vulnerabilities by pairing Corti’s clinical-grade governance frameworks with localized European supercomputing compute. The platform is anchored by DCAI’s ISO-certified Gefion AI supercomputer, which is expanding via a scalable NVIDIA Blackwell B300 cluster to serve as a sovereign national and regional inference backbone.
“European enterprises need access to the world’s best AI models without becoming dependent on a single provider. Corti Models gives organizations the flexibility to innovate while staying in control of their data, compliance obligations, and long-term AI strategy.”
— Andreas Cleve, CEO and Co-Founder, Corti
To eliminate engineering friction, the architecture features a single, drop-in OpenAI-compatible API that supports sovereign cloud and on-premises environments, allowing engineering teams to change inference endpoints without rewriting backend application logic, prompts, or evaluation datasets. The initial deployment focuses heavily on enterprise software development and agentic coding, keeping proprietary codebase data strictly within European jurisdictions while cutting developer AI spend by up to 5–10x through centralized, consumption-based budget governance.
