Defending against the threat of drones–Droneshield

Nov 12, 2025

Oleg Vornik, CEO of DroneShield, leads a company building RF and multi-sensor systems to detect and defeat hostile small drones. He discusses why non-kinetic defeat is safer than shooting drones. He explains moving to on-device micro AI and building the world’s largest drone signal library. He maps growing civilian demand from airports to data centers and the ongoing cat-and-mouse with drone makers.

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INSIGHT

RF Is The Detection Backbone

Radio frequency (RF) is the primary detection method because drones communicate telemetry and control over RF.
Secondary sensors like radar, cameras and acoustics supplement RF for edge cases.

ADVICE

Avoid Kinetic Defeat In Civilian Areas

Prefer non-kinetic defeat methods because shooting is unsafe and not cost-effective against cheap drones.
Use techniques that confuse or disable drones while remaining harmless to humans for mass adoption.

INSIGHT

Micro AI For Constantly Evolving Drones

Counter-drone is now an AI problem because drone protocols and models proliferate rapidly.
DroneShield built a global signal library and plans 'micro AI' to run self-learning models on tiny, offline devices.

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We're in Sydney with Oleg Vornik, CEO of DroneShield, makers of radio-frequency technology to detect and take down small, hostile drones across 50 countries. While defence demand is rising, airports, data centers, and infrastructure facilities are also looking for protection against small drones used for surveillance, cyber threats, and sabotage.

Learn how DroneShield built the world's largest drone signal library, why simply shooting down drones isn’t viable, and why they’re moving to "micro AI" on tiny, self-learning devices. Hear about the “cat and mouse game” between counter-drone developers and drone manufacturers, constantly innovating to avoid detection.

Plus, find out why Oleg believes counter-drone activity in public spaces like airports, stadiums, and prisons will grow as drones become a fact of life.

This episode was recorded on 15 October 2025. All commentary reflects the timing of the original conversation.

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