Unclassified // Public Release · Capability outcomes only
Built for · DoD program offices

Open interfaces, one human gate, and a record of every call.

A program office is buying risk reduction before it is buying capability. DaggerOS is built so the three risks you have to answer for — accountability, autonomy, and lock-in — are retired by design.

What you get

Why DaggerOS fits your mission.

Lower program risk

Built to a Modular Open Systems Approach on published interfaces. The government owns the interface and the mission data; commercial software licensed per DFARS 227.7202. See the data-rights posture.

An ATO path you can actually walk

Designed against what an assessor reviews: NIST RMF 800-37 and the 800-53 controls catalog, with an air-gapped, passive-default posture that shrinks the external attack surface.

Autonomy risk, retired

Human-in-command by architecture, aligned to DoDD 3000.09. No autonomous engagement path exists — and you can test the gate yourself.

Maturity you can cite

TRL 7–8, demonstrated under live, operationally representative, third-party conditions at T-REX 26-2 (May 2026). Demonstrated, not certified — stated plainly.

Bring the standard your office evaluates against and the acquisition pathway you prefer — FAR Part 12, OTA, SBIR Phase III, or firm-fixed-price. DaggerOS is aligned to all four.

Straight answers

DoD program offices — common questions.

Can DaggerOS get an ATO?
It is designed against the path an assessor reviews — NIST RMF 800-37 and 800-53 — with an air-gapped, passive-default posture and human-in-command enforced in the architecture. BlackByrne does not claim a granted ATO; it builds toward the accreditation path.
Who owns the data and the interface?
The government. DaggerOS is commercial software licensed per DFARS 227.7202; BlackByrne retains title to its own IP, and the government owns all mission data and outputs.
What acquisition pathways fit?
FAR Part 12, OTA, SBIR Phase III sole-source, and firm-fixed-price. See the acquisition pathways guide.

Bring us a problem that spans domains.

One operator should hold it. The AI recommends. A human decides.