Nefeli Air

The proliferation of small, RF silent, and non-metallic unmanned aerial vehicles (UAVs) presents a significant challenge in modern conflict scenarios. These drones, often constructed from non-metallic materials and operated via fiber wires, can circumvent traditional radar and RF jamming systems, creating a critical capability gap for defense and security organizations in detection, tracking, and neutralization, particularly in air-to-air interception.

Falconix AI addresses this vulnerability with an AI-powered system designed for the detection and interception of such elusive aerial threats. The system's core strength lies in its RF silent detection capabilities, which employ Electro-Optical (EO) and Infrared (IR) sensor video feeds. This visual data is processed by edge-optimized neural networks, enabling the identification of threats that are otherwise invisible to conventional radar or RF jamming countermeasures.

Key operational features include autonomous interception functions that dynamically guide interceptor UAVs for immediate engagement with identified threats. Furthermore, the system is engineered to be hardware agnostic, facilitating seamless integration with a diverse array of existing UAV platforms. This adaptability enhances its deployment potential across various operational contexts.

Falconix AI primarily serves defense and security forces, operating within the specialized market of counter-drone technology. The business model likely involves direct sales of its detection and interception system to governmental defense agencies or to defense contractors integrating such capabilities into broader security solutions. Revenue generation is anticipated through system sales, software licensing, integration services, and potentially ongoing support and upgrade contracts.

Keywords: Counter-UAS, Drone Detection, AI Security, EO/IR Sensors, Neural Networks, Autonomous Interception, RF Silent Drones, Defense Technology, Air Defense, Hardware Agnostic