Capital
Why IntelligentX
We sell outcomes, not GPU hours
GPU-leasing neoclouds price per GPU-hour or per megawatt, to a handful of very large buyers. IntelligentX prices per application, workload and seat across a governed platform, to hundreds of enterprise and government accounts.
Others are building AI factories for a handful of model labs. We put compute where the customer needs it: in our regions, sized to signed demand, or in the customer's own data center or cloud. Our capital goes into customers and software.
| Build-model neocloud | IntelligentX | |
|---|---|---|
| Capex | Billions in power, land, GPUs and networking | Racks in existing facilities, bought in tranches against signed contracts |
| Time to revenue | 12 to 36 months of power and buildout | Weeks to months. Colocation space and power are already built |
| Technology risk | Gigawatts of one GPU generation | Small tranches, so each purchase lands on the current generation; burst via in-country GPU partners |
| Capital efficiency | Debt-heavy, GPU-backed facilities | Software margin on every hour of compute |
| Where it runs | Their data centers only | Our region, your data center or your cloud |
| Sovereignty | Varies by ownership and site | Tenants pinned to one country, operated in-country, policy enforced by Zetaris |
Capability
What a typical neocloud ships, and what we ship
| Capability | Typical neocloud | IntelligentX Cloud |
|---|---|---|
| GPU and CPU infrastructure | GPU only, gigawatt-scale | GPU and CPU, region by region |
| Sovereign positioning | Partial, by site | Policy-enforced |
| Data virtualization and semantic context | Via partners, if at all | Native Zetaris |
| AI application generation and deployment | Limited | PIES Studio |
| Private fine-tuned enterprise LLM | PIES private models, LoRA-tunable | |
| Built-in governance and audit | Platform-level | |
| Capital intensity | Very high | Low |
| Revenue model | GPU leasing | Platform plus compute subscription |
Why now
Three shifts, one window
- 01Supply is turningGPU supply moves from scarcity to oversupply as gigawatt builds come online. Forward-buy pricing favors buyers; raw compute margins compress.
- 02Enterprise AI is going to productionPilots become production and agents. The constraint is context and governance, not FLOPs.
- 03Sovereign mandates reward policyUS state privacy laws, sector rules like HIPAA and GLBA, and sovereign mandates in Australia and Europe all reward providers that enforce policy. Owning a building is not enough.
The winners of 2028 will not be the clouds with the most GPUs. They will be the ones whose GPUs are busy running the enterprise's own intelligence.
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