In an era of generative audio and synthetic media, disinformation is no longer just visual — it speaks. With UnCognito™, organisations can detect and stop deepfake voices in real time, before they cause reputational damage, political fallout, or public panic.
Deepfake voice technologies now allow anyone to clone a public figure's voice from minimal samples, fabricate audio leaks or commands, and bypass voice authentication systems. The common response — more AI to fight AI — creates an arms race defenders cannot win.
UnCognito's approach is different: physics-based, deterministic detection with roots in passive sonar — not black-box ML guesswork. The result is a closed-loop system that is stable under adversarial iteration, operates offline, and runs in real time with a minuscule resource footprint.
And beyond cybersecurity, the same physics-first expertise extends directly into national defence — passive acoustic drone detection, battlefield edge deployment, and automated response systems.
Operating across cybersecurity and national defence — two markets with converging threat vectors.
No need for large AI inference pipelines — physics-based checks run efficiently in real time.
As attackers iterate on generative models, our detection does not degrade — it remains anchored in physical reality.
Deployable offline, at the edge, in classified environments — where heavyweight cloud AI cannot go.
Decades of signal detection expertise from the most demanding passive sensing environments.
High-fidelity seismic and acoustic signal processing at scale — the foundation of our physics-first approach.
Real-time, low-latency systems built for environments where failure is not an option.
Not naive AI — we know where AI works and where physics outperforms it. We use both where each excels.