AI-ready data centre in Pittsburgh
AI-ready data centre in Pittsburgh
Why choose Pittsburgh?
- Home to globally recognized, top-tier research institutions.
- Proximity to East Coast and Midwest markets.
- Available clean energy sources, such as hydro and wind.
- Close to financial hubs and growing AI ecosystems.
Key benefits
135+ kW high density computing racks
Designed from the ground up for GPU clusters and large-scale compute, enabling from advanced model training to high-frequency trading environments.
Rapid time to deployment
With 2.4 MW IT capacity available now and a clear path to 12 MW IT total by 2027, you can scale in line with your roadmap, without waiting on infrastructure.
Energy efficiency & ESG alignment
Our closed-loop cooling and support for direct liquid cooling (DLC) drastically reduce PUE and footprint, allowing performance and sustainability to coexist.
Key value
- Rapid scalability, allows fast deployment.
- AI/HPC-focused infrastructure designed for compute-heavy, high-throughput environments.
- High-density racks supported, energy-efficient site design.
Who it’s built for
Whether you work for a university that’s expanding its research capabilities, a startup scaling multimodal models, or an AI infra provider launching in the U.S., our data center is ready when you are.
- Accelerate AI and HPC research with scalable, high-density colocation near Pittsburgh, solving the problem of building campus space, finding more power, and compliance challenges.
- Gain full control over your AI infrastructure with flexible, rack-ready colocation, eliminating the unpredictability of cloud costs and speeding up time to market.
- Quickly deploy in the Eastern U.S. with rack-ready colocation, avoiding build costs while gaining low-latency, AI or HPC-ready infrastructure.
Use cases
AI/ML model training and inference
High-performance computing used for simulations in science and finance
Hybrid and private cloud environments for regulated industries
Efficiency
Closed-loop cooling systems
DLC support to reduce environmental impact
Energy efficiency by design (target PUE as low as 1.15)
