AI & HPC

GPU compute · Scheduling · Inference

Compute scheduled, monitored, and kept inside its boundary.

Start a conversation Part of: For government

Two graphics cards laid on black, fans and shrouds in close-up — Plate № 01Accelerator hardware

What it covers

A cluster is an infrastructure problem.

The newest of the four sheets — capability, not history.

Underneath the accelerators, it is infrastructure — and gets the same treatment.

Capability

What we can design and run.

Read the maturity row. This one is stated as capability.

Data sheet

Discipline: GPU and high-performance computing.
Built as: Scheduled, partitioned clusters defined in code.
Serving: Model-serving stacks, including self-hosted LLM inference.
Data: HPC pipelines — staging, throughput, retention.
Boundary: Inside the boundary, no assumed egress.
Maturity: Capability and architecture, not delivered programs.
Route: Under a prime, as subcontractor.
You own: The cluster definitions, images and models.

Capabilities

GPU nodes provisioned from code.
Scheduling with queues, accounting, per-project limits.
Partitioning — one card, several jobs, safely.
Model serving: versioned, capped, behind your identity.
No model phones home, by design.
Pipelines sized to keep the hardware fed.
Encrypted, backed up, logged, inside the boundary.

Stated as capability. We are not claiming a delivered government AI program. No agency, no model of record. TS/SCI clearances are held by individual engineers, applied through teaming; Stagg Business Solutions Inc. holds no corporate facility clearance.

Registrations

CAGE 149Y3
UEI WHRZRJNG39L5
NAICS 541512

In our commercial work

The compute is new. The discipline is not.

What we bring is the operating practice.

The inside of a machine — cooling fans, memory and cabling, lit from within — Plate № 02Compute, up close

What is running today

Infrastructure defined in code, so it rebuilds.
Encrypted volumes and scheduled snapshots.
Multi-factor identity, access by role.
Metrics and dashboards, so "is it slow" has an answer.
Audit logging and threat detection from day one.
A read-only data feed over a private network.
Self-hosted inference, our hardware, our network.

Commercial and internal. Everything above is commercial work, or our own infrastructure. None of it is a government contract award or an AI program of record.

The other three

Four practice areas, one team.

These three are what compute sits on.

Next step

Talk to the engineers.

A capability question, a teaming conversation, an environment.

Email: [email protected]
Phone: (801) 917-4617
Base: Utah — Mountain Time · replies within 24 hours
Registrations: CAGE 149Y3 · UEI WHRZRJNG39L5 · NAICS 541512

Start a conversation The commercial side