Solutions
We support institutional workloads across three primary domains today, with room for use cases that fit our operating model.
AI and machine learning
Training, fine-tuning, inference, and deployment of large language models, multimodal systems, computer vision, and enterprise AI applications.
Typical customers: European AI companies and technology scale-ups building on open-source or commercially permissible models.
Financial and quantitative
Quantitative analysis, time-series forecasting, portfolio modelling, AI-assisted analytics, and related computational workloads.
Typical customers: private banks, fintech companies, and asset-management firms. Private institutions only.
Research and HPC
Scientific computing, physics simulations, climate modelling, computational biology, and other high-performance computing workloads.
Typical customers: academic institutions and private research organisations.
Other use cases?
The three areas above are where we see the strongest fit today, but they aren't the only ones. If your workload falls outside them but operates within the policies we follow — institutional customer, contracted access, no prohibited use — we're open to a conversation.
What we ask
- A short description of the workload and its purpose.
- Who the customer organisation is and what jurisdiction it operates from.
- Approximate compute scale and timing.
We respond either way. If something doesn't fit, we say so directly.
Out of scope
Some workloads fall outside what we support. The Trust page sets out the full picture. If you're not sure whether your case fits, get in touch.
Discuss your workload.
Tell us what you're building. We'll let you know whether and how we can help.