Governed AI compute on a heterogeneous GPU fleet — enterprise, program office, or your own data centre.
AI Command and Control is a packaged desktop application over a governed substrate: your GPU fleet across clouds and hardware classes, the agents that act on it, and a boundary that decides what each agent may do.
The console never decides anything itself. It issues intents; the substrate enforces them; and every decision lands in a tamper-evident record with the reason attached.
Fleet, placement, observation and containment in one application.
Every machine as a node in a capability graph — GPUs and other substrates — linked live to the fleet.
Search by capability and compose a fleet from what is actually available, not from a catalogue.
GPU offerings across clouds, compared and ranked — the utilization lever, not only the cost lever.
Live telemetry straight from the hardware rather than through a polling proxy.
What a machine advertises versus what was verified on it. The gap is the finding.
Work placed by capability across clouds and hardware classes, with authorization decided on the same graph.
Every link into the fleet is an encrypted, access-controlled connection whose status is verified rather than assumed.
Energy, performance and claim tests run against the hardware itself, with results kept.
A capability graph decides what an agent may reach, a disallowed action is refused before it runs, and every decision is recorded.
The governance layer is identical everywhere. What changes is where the agent runs.
A local virtual machine for demonstration and development at zero cloud cost.
Ephemeral, per-agent isolation at scale.
Elastic capacity across providers and local clusters, governed as one fleet.
Owned GPUs in a private data centre — sovereignty, data locality, and the most out of hardware you already own.
Deployed from the same console — and governed like any other call.
Chat with persistent conversation memory. Retrieval over graph and vector stores is served as governed tools, so it is decided and recorded like any other call.
An agent that runs on hosted model providers or a local model, calling tools discovered from a registry — every tool call governed at the boundary.
Per-tenant model token metering, quota and cost, so spend is a ledger rather than an invoice.
Fine-tuning and inference placed on GPUs you choose, with energy measured per unit of work. Large-language-model training and serving are specified on the same fleet and are next.
A hosted model service rents inference behind an API. AI Command and Control governs agents on GPUs you control. They answer different questions.
An aircraft, a ship, a secure facility. No cloud API is reachable; the boundary runs on the hardware that is there.
Large owned GPU estates cannot be used by a hosted service. Utilization of sunk hardware is the lever.
One console and one governance layer across several providers, rather than one provider’s service.
Content filters screen text. Agents act. What an agent may do — and the recorded basis for the answer — is what an authorizing official asks for.
Self-hosted weights, and the freedom to change model provider without changing the console.
Energy per unit of work, measured from the hardware. At the edge, that is the constraint.
Not instead of hosted models. Hosted services where they are authorized and connected; your own GPUs where they are not — one governance layer over both. An agent in the sandbox may still call a hosted model, and that call is decided and recorded like any other.
An assistant working through a code graph and an embedding index can query and diff freely — those actions are reachable from the goal in force, and the path is recorded.
Dropping a database, deleting an index or reading a credential is refused — not by a rule written against each one, but because no path to it exists. That is why the approach scales to commands nobody anticipated.
Every answer, allowed or refused, carries the basis that produced it.
A live demonstration against running sandboxes, and the architecture behind it, is available under NDA.
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