Training workloads cluster at gigawatt campuses. Inference lives at the edge — cell towers, hospitals, telco co-los, sovereign nodes. The compute market is splitting in two directions, and the infrastructure underneath has to follow. We build for both. One modular foundation. Four physical formats. Same delivery discipline at every scale.
Inference compute belongs where the users are. Cell towers, hospitals, retail anchors, telco co-los, government facilities. Sub-megawatt modular pods deployed in distributed fleets — locking the layer of infrastructure that almost no one is building for yet.
Training is hyperscale. Inference is everywhere. As AI moves from model development to widespread consumption, the compute layer has to follow the user — and ultra-low-latency delivery requires infrastructure that lives at the edge of the network, not in a gigawatt campus three states away.
We built our platform for both halves of that picture. The same factory that builds our campus pods builds the sub-megawatt pods that drop into cell tower compounds, hospital backlots, and telco facilities. The distributed edge layer that inference economics actually require is something we manufacture, deliver, and operate today — not a future workstream.
Hundreds of megawatts of distributed capacity across thousands of edge sites — a network nobody is building yet. The next layer of the AI compute stack.
Multi-site clusters in the 1–10 MW range. Regional inference deployments, enterprise pilots, federated training across geographies. The pod count scales up, the deployment discipline stays identical to the edge.
Between edge nodes and full campuses sits the distributed tier — multi-site programs where regional latency, sovereignty boundaries, or anchor-tenant economics call for several million-watt sites instead of one big one. Enterprise AI pilots, federated regional inference networks, and sovereign workload portfolios all live here.
Same modular factory. Same delivery discipline. The customer gets a fleet of sites, not a single point of capacity — with operational uniformity that single-site builds can't match.
Behind-the-meter generation on dedicated acreage. Training-grade workloads. Single anchor tenant or anchor-plus-multi structure. The model the market knows — built with modular discipline instead of stick-built risk.
Where dedicated training capacity matters — multi-hundred-megawatt single-site deployments serving anchor tenants requiring concentrated GPU clusters. The pod-based delivery model means capacity activates in waves rather than waiting for the whole site to commission, and refresh cycles compound the long-term value.
Behind-the-meter generation eliminates the interconnect-queue exposure that defines every traditional grid-tied campus build right now. The site is operational on company-owned power infrastructure while utility tie-in proceeds independently.
Federated multi-site programs at gigawatt scale. National platforms, sovereign capacity portfolios, hyperscaler partnership programs. One operating system, many physical sites, delivered as a coordinated program rather than a one-off build.
At the largest scale, customers are no longer buying a building. They're buying a program — multi-gigawatt capacity across multiple sites, multiple regions, coordinated under a single operating model. This is where the modular thesis becomes unanswerable: no traditional builder can deliver gigawatts of distributed capacity on a coherent platform. The model that builds one site builds all of them.
Site selection, manufacturing throughput, power partner relationships, and capital structure all scale linearly. The 300th megawatt deploys the same way the first one did — with the same delivery discipline, the same refresh model, the same operational uniformity.
Model training concentrates compute at gigawatt campuses where the cluster economics and chip-to-chip bandwidth demand a single location. Inference does the opposite — it follows the user, requires sub-millisecond latency, and scales to wherever people actually consume AI products. We built the platform to serve both.
The same modular pod design deploys at sub-megawatt cell-tower compounds and at multi-hundred-megawatt campuses. One platform, both halves of the picture, the same delivery discipline at every scale.
Submit a capacity inquiry. Tell us the workload, the scale, the timing. We respond with a fit assessment.