Phinorm builds sensor-agnostic software that classifies airborne targets for counter-drone systems. We take raw sensor data, decompose the signals, and tell operators what's in their airspace. Our approach is rooted in a rediscovered mathematical framework with patent-pending applied innovations that make it work on real battlefield data. Software-only, runs on edge hardware, works across radar and acoustics. We don't sell sensors. We make existing ones smarter.
Counter-drone systems can detect objects but can't reliably identify them. Operators are left guessing under time pressure, which leads to missed threats or friendly fire incidents. The global C-UAS sensor market is $22B and growing at 25-33% CAGR. Everyone is buying detection hardware. Almost nobody has solved classification especially in the size, weight power and cost constrained environments where it's needed most .
3x accuracy improvement over next-best published state of the art approach on radar classification, lab-validated at TRL-4. Invited to Ukrainian testing ranges for field trials off two PoCs. Integration LOI and MOU with ongoing joint R&D with Fraunhofer. Actively engaging with DIU, DARPA, UK MoD, NATO and Singapore DTSA. Patent applications filed on core innovations.
