SCALABLE, OFF-GRID, AND READY TO DEPLOYData Centers
AI workloads require high-density, high-efficiency compute environments, but many legacy data centers weren’t built for this scale. They can take years to construct, struggle with inefficient cooling, and drive up costs due to outdated power architectures. AI needs a new kind of data center—built for the future, not the past.
“Global demand for data center capacity could more than triple by 2030, with estimates ranging from +19% to +27% CAGR.”
A Network of Colocation Partners
Through a series of strategic partnerships with vetted data centers across the country, we aim to rapidly deploy GPUs more rapidly than hyperscalers.
Power Integration Strategy
Our owned data center strategy is not solely reliant on the grid. Future expansion plans include the potential to access 100+ MW of behind-the-meter natural gas.
Hyperdistribution for Low-Latency AI Inference
Instead of concentrating AI capacity in a few hyperscale data centers, we intend to reduce round-trip latency by expanding AI access beyond major metros
Global Demand for Data Center Capacity Could Triple
DATA CENTER CAPACITY DEMAND IN GIGAWATTS[One] possible scenario sees demand rising by 27 percent to reach 298 GW. [...] To avoid a deficit, at least twice the data center capacity built since 2000 would have to be built in less than a quarter of the time.
Source: McKinsey & Company
