The AI Cowboys

Edge, on-prem & air-gapped AI

Edge, on-prem and air-gapped AI for systems that cannot phone home.

Most AI assumes a data center and a fast connection. We build the kind that runs on the platform or inside your perimeter: small language models on your own servers, perception on a drone or a sensor, and digital twins on an air-gapped floor. When the network is gone, it keeps working, and your data never leaves.

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Three ways to keep AI inside the perimeter

The words get used loosely, and the difference matters for security review, cost and maintenance, so we define them up front.

Private and air-gapped language models

For document search, drafting, classification and agentic workflows on sensitive data, we deploy small and large language models on your own hardware: open-weight models, fine-tuned or retrieval-grounded on your corpus, served from inside the enclave. Small language models are often the right call here. They fit on modest hardware, respond quickly and are easier to evaluate, and our work on small language models and agentic AI has been recognized by LlamaIndex and NVIDIA.

The engineering is mostly around the model rather than in it: how weights are transferred and verified, how the retrieval store is built and access-controlled, how updates cross the gap, how outputs are logged for audit, and how the system is evaluated inside the perimeter rather than against a public benchmark.

Perception on a power budget

At the far edge, the constraint is watts. In our San Antonio lab, a hybrid NVIDIA Jetson plus BrainChip Akida deployment held the same accuracy at 9 W that the Jetson alone needed 120 W for. That is the difference between a perception system that needs a vehicle's power supply and one that runs on a battery.

Digital twins that never leave the floor

A live, sensor-fed model of a facility or a fleet is exactly the data that should not transit someone else's infrastructure. We build digital twins whose sensor feed, model and analytics all run on-premises or air-gapped.

Security and compliance practice

Our deployments follow secure software development practice under Executive Order 14028, ship with a software bill of materials, and are aligned to the NIST, CMMC and FedRAMP frameworks federal and regulated buyers are held to. We can also test a system someone else built through our independent validation practice.

Questions about edge, on-prem & air-gapped ai

What is an air-gapped AI system?

An air-gapped AI system runs on hardware with no network connection to the outside. Models, updates and data are moved across the gap deliberately on controlled media, verified and logged, so prompts, documents and outputs never leave the protected environment.

Can a large language model run on-premises?

Yes. Open-weight language models can be served from your own servers, grounded on your documents with retrieval or fine-tuning, with no calls to an outside AI provider. Smaller models often suit on-premises use because they need less hardware and are easier to evaluate.

What is the difference between edge AI and on-premises AI?

Edge AI runs on the device in the field, such as a drone or a sensor. On-premises AI runs on servers in a facility you control. Both keep data local; edge AI is constrained mainly by power and size, on-premises AI mainly by your server capacity.

How are models updated in an air-gapped environment?

Updates are packaged outside, checked against published hashes or signatures, carried across on approved media, verified again inside, tested against an internal evaluation set and only then promoted. Every step is logged so the change history is auditable.

Do you deploy in the customer's own cloud?

Yes. Everything we build deploys on-premises, air-gapped, or in the customer's own cloud account, so the customer keeps control of the data and the infrastructure.

Go deeper

Start with a briefing: one real problem, the constraints around it, and what a scoped pilot would measure.

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