Safety is how we build.
Fielding software into contested environments demands a higher standard. Safety is not a checklist — it is an engineering discipline applied at every stage.
Fielding software into contested environments demands a higher standard. Safety is not a checklist — it is an engineering discipline applied at every stage.
Before software reaches an operational unit, we expose it to small, controlled operator groups and instrumented test ranges. We observe, measure, and iterate before widening fielding.
We run layered evaluations — automated regression, recorded-data replay, and human review against mission threads — to verify every release against defined performance thresholds. Failures hold the release.
Independent researchers, adversarial-ML specialists, and operators on the mission attack our systems. That includes spoofed and degraded sensor inputs, data poisoning, and probes for unintended autonomous behavior. Findings harden the system.
Every new capability is assessed against tracked risk categories before it ships. A high risk rating in any category requires safeguards before release — no exceptions.
Preparedness framework
Every new capability is evaluated against a defined set of risk categories before it ships. A high rating in any category triggers mandatory safeguard work — deployment is gated until the risk is addressed.
Systems that act in the physical or tactical environment must have bounded authority and a clear path for human intervention. We impose hard constraints against self-directed escalation and test for scope creep.
We assess whether models or pipelines could be spoofed, poisoned, or used for lateral movement into operational networks — and build against it from the start.
We evaluate performance under degraded, adversarial, and shift conditions — night, clutter, contested spectrum — so performance claims hold in the field, not just in the lab.
Ongoing work
Every deployment generates signal. Operator feedback, anomaly detection, and model monitoring feed a continuous loop of evaluation and improvement. We review emerging findings and update our policies as capabilities and threat models evolve.
Safety is not a team — it is a property of how the company operates. Every engineer is accountable. Every model has an owner. Every incident has a postmortem.
We are looking for researchers, domain experts, and operators who want to find failure modes before they happen.