Running Private AI

Private AI: Fit First.

Highly Private
Micro Models

Public Frontier
Macro Models

Frontier AI systems like ChatGPT and Claude capture headlines, but the AI landscape is much larger. At the other end are tiny internal models doing specific domain work, sometimes with no Internet connection at all. nFOX helps teams find the right fit, then deploy the operational controls appropriate to the model, data, infrastructure, and risk.

Map Your Private AI Path Technical Specs

Sovereign AI Definition

What sovereign AI means.

Sovereign AI is stricter than private AI. A private deployment may reduce exposure, but sovereign AI means you deploy, operate, and refine AI entirely within a controlled envelope that the enterprise can approve, inspect, and govern.

If a single prompt, vector, generated token, tool call, runtime service, model artifact, or audit path crosses outside the entity's control framework, sovereignty is broken.

The Sovereign Envelope

Prompts and responses stay inside approved control paths.
Vectors, retrieval data, and tool calls stay under enterprise policy.
The model runtime runs on infrastructure the enterprise controls.
Logs, audit records, and operational evidence remain inspectable.

Why GPU Deployment Matters

Managed inference endpoints can move runtime control outside your boundary.
Shared GPU pools and opaque hosting can blur data, process, and audit ownership.
Dedicated GPU VMs, rented GPU boxes, and owned hardware need different evidence.
nFOX maps the deployment model against the sovereignty claim before production.

Enterprise Operating Model

Running AI is an incredibly valuable operating discipline.

nFOX helps you run AI. Start with a contained experiment. Then choose the right isolation, model shape, and evidence path before sensitive work moves in.

Read the field note

What You Get

IP stays inside infrastructure you control.
Focused models for enterprise logic.
Activation traces and operating evidence.
Blockhouse sandboxing and controlled comms.

What It Takes

Match isolation to data and workload risk.
Understand model behavior before trust.
Choose RAG, fine-tuning, or dedicated models.
Review evidence as part of operations.

Next Step

Bring private AI under control before it sprawls.

We can map your model sources, GPU hosts, runtime choices, and evidence needs against the nFOX workflow.

Talk to nFOX