MatrixSpace is deploying an AI-native, multi-sensor platform that fuses data at the tactical edge and coordinates it through the cloud to deliver faster, more reliable detection of low-altitude drones.
The platform aims to improve situational awareness in complex airspace environments where small, low-flying drones are increasingly difficult to track.
It’s built around two core components: AiEdge and AiCloud.
AiEdge operates at the tactical edge, combining data from radar, optical sensors, and identification sources in real-time. This produces cleaner tracks, filters out clutter, and allows operators to identify potential drone threats quickly.
Assessments from AiEdge are shared with AiCloud, which aggregates data from multiple sensors to create a single, coordinated picture of low-altitude airspace.
By centralizing real-time activity, AiCloud provides situational awareness across multiple sites simultaneously.
“Most traditional systems rely on noisy, exotic sensors with siloed, cumbersome command and control (C2) structures that hinder decisive action,” said Matt Kling, Vice President and General Manager of AI Systems at MatrixSpace. “But as threats of drone detection get only more complex, they require instant ‘threat truth.’”
MatrixSpace designed the platform to support a wide range of operating environments, from fixed sites such as stadiums, ports, ships, and government facilities to mobile deployments that can be rapidly set up and relocated.
Each site maintains its own edge-based detection while staying connected to the broader network, providing real-time situational awareness across locations.
