Airman
Vision

See threats. Keep secrets.

Private, on premises AI for security, vision and cyber defense. One software platform, running on NVIDIA GPUs inside the customer's own walls.

Private AI and Vision prototypes running today on local NVIDIA hardware

Wireframe stealth fighter in a camera targeting frame

The problem

Security teams want AI.
They cannot ship their data to someone else's cloud.

01

Cameras cry wolf

Most video analytics alerts are false alarms. Guards learn to ignore them, and the real threat gets lost in the pile.

02

Cloud AI leaks

Law offices, schools, municipalities and defense suppliers cannot send sensitive footage, documents or network logs to a public model.

03

Compliance is a burden

CMMC and rules like it demand evidence and monitoring that small teams simply cannot staff.

Airman Vision puts the models, the data and the audit trail on hardware the customer owns.

The platform

One platform. Three modules.

The same software stack runs on every size of system: CUDA, TensorRT, Triton, DeepStream, Morpheus, Nemotron models, private retrieval and disk encryption. Upgrade the GPU, not the software.

AIRMAN VISIONOne software platform on NVIDIA GPUs
Prototype running

Private AI

A local LLM workspace with private retrieval over the customer's own documents. No data leaves the building.

How it works →
Prototype running

Vision

Firearm, aggression, fall, loitering, and fire and smoke detection, with a vision language model second check on every alert.

How it works →
Planned

Cyber defense

A network defense agent and a CMMC compliance agent on NVIDIA Morpheus, reading traffic locally.

How it works →

The second check

Every alert is re read by a vision language model before a human sees it.

1Detector firesA fast YOLO class model flags a clip
→
2VLM reviewFrames plus a prompt: is a person holding a firearm? Explain.
→
3DecisionConfirm, downgrade or suppress, with the reason stored
→
4HumanThe operator sees a verified alert and the explanation

Cheap first, smart second

The fast detector runs on every frame. The slower VLM only runs on flagged clips, so cost stays low.

Auditable

Each decision keeps the clip, the prompt, the VLM answer and the operator action for later review.

Architecture

Detect at the edge.
Reason in the core.

Jetson units at the camera run the detector on the live stream. An Airman Vision server on site handles the second check, footage search, analytics and agents. A DGX or the customer's own private cloud is optional, for heavy VLM work, fleet analytics and retraining.

Raw video stays on the edge or site box. Only alerts, metadata and clips the customer approves move upstream.

Security camera lens glowing in the dark

Footage search

Ask your cameras a question.

Person walking past a loading dock at night

Example queries

“Person in a red jacket near the loading dock after 6 pm.”

“Show every vehicle that stopped at gate 2 last night.”

Planned. Built on the NVIDIA video search and summarization blueprint. Clips are embedded, captioned and indexed on the site box, and nothing is sent to an outside service.

Follow the work

Prototype. Benchmark. Pilot. Ship.

Every figure we publish will come from our own runs on named hardware, with scripts alongside. Researchers, NVIDIA developers and security practitioners are welcome to compare notes.

airmanv@gmail.com