Fullscale designs, manufactures, and deploys the modular units that AI compute runs on. From a single unit at the edge to a multi-gigawatt campus.
Modular units engineered around the workload that runs inside them. US-manufactured. Configurable cooling, density, and connectivity. Site preparation runs in parallel with factory assembly.
Standardized units. Configurable cooling, density, and connectivity. Engineered to spec, manufactured to schedule.
Site selection driven by energization speed. Source-flexible by design. Smart utility alignment from day one.
Hardware moves in eighteen-month cycles. Swap units between generations. Stay current. No forklift rebuilds.
Single-unit and small-cluster deployments. Cell towers. Hospitals. Remote installations. Sovereign edge. Discrete footprint. Fast install. Same modular DNA as the campus deployments.
Edge model →
The flagship deployment of the Fullscale platform. Multi-unit power blocks. Anchor tenants. Hyperscale workloads. Dual-path energization. Expansion architecture on the same footprint.
FS-1 Campus →Power is the binding variable on AI infrastructure timelines. Fullscale sites are selected for fast energization, designed source-flexible from the ground up, and engineered in partnership with utilities for the long-term scale path — behind-the-meter, grid, or hybrid, whichever combination delivers fastest with the cleanest expansion economics.
GPU generations turn over every eighteen months. Traditional data centers can't keep up — the cooling, density, and power assumptions are poured into concrete the day they open.
Fullscale units are designed to be swapped. When the next generation arrives, the old unit is pulled and the new one rolls into the same site.
Communities are increasingly opposing conventional data center developments — and for good reason. They are loud, large, and disruptive. Eighty-foot industrial buildings. Years of construction. Permanent visual impact.
Fullscale units are different. Single-story. Quiet. Discrete. Manufactured off-site and installed on prepared ground. They fit into a community instead of overwhelming it.
Our community approach →
Cloud providers and AI labs that need rapidly deployable capacity at hyperscale. Power and timeline certainty matter as much as the gigawatts.
Neoclouds, training and inference platforms, and GPU cluster providers scaling fast on AI-workload timelines.
Telecom infrastructure, healthcare systems, remote installations, and sovereign deployments where compute lives.
15+ years founding, scaling, and exiting technology companies. Deep experience integrating tech systems with physical infrastructure buildout.
25+ years of multi-site physical operations and heavy equipment implementation. Owns Fullscale's manufacturing, supply chain, deployment, and commissioning stack.
30+ years in institutional capital markets. Capital architecture for infrastructure-scale platforms — debt, equity, and project finance.
Capacity commitments and edge deployment partnerships are open. Tell us your workload, your scale, your timeline.
