Smarter sensors.
Lighter hardware.
Air defenses are bombarded with sensory overload. When every second of warning saves lives, Phinorm improves detection through a simple software upgrade — faster, more accurate, ready to integrate.
Sensors change. Models break.
Neural networks often struggle to adapt quickly when operating conditions shift (environment, platform, clutter, sensor swap, domain shift). In small-sample settings, retraining costs time and compute — exactly when you can’t afford delay.
Neural networks fail to adapt quicklyRapid adaptation with trade-off free math.
Phinorm uses a “forgotten” mathematics branch that combines with other AI approaches to converge quickly to new settings, while staying compute-efficient and deployable on any device.
Adaptive / resilient across environmentsWhy Phinorm
Better signal filtering with less compute — suitable for embedded and edge deployments.
2–4× fewer errors versus scientific benchmarks in small-sample radar classification.
Robust in changing environments — designed to work on any device.
A mathematics approach that can complement (not replace) existing ML stacks.
Position Phinorm as a drop-in software upgrade for sensing pipelines.
Radar, acoustics, visual & vibration — reuse the approach across modalities.
Small-sample bird vs drone radar classification
Neural networks fail to adapt quickly.
Best benchmark model** (ensemble with FFT).
Rapidly converges to new settings.
Leadership team
Philipp Gschoepf
Built 2 AI CoEs (250 staff), delivered 219 AI programs to $450M impact (4x ROI) in highly confidential data environments.
David Behrens
AI researcher, quant consultant at Deloitte; radar signal specialist.
John Fabros
Former P-3C Naval Flight Officer; 1,100 hrs and Air Medal recipient; led $10M+ intl defense acquisitions programs.
Active TS/SCIElina Conley
Defense go-to-market, government partnerships, and IP licensing; managed 40+ DOE SBIR/STTR Phase I/II projects.
Rostam Assadi
Advised DoD on tech investment; advisor to G20 heads of state.
Board of Directors
Mus Chagal
Experienced CEO and board member in the DoD portfolio space focused on critical military applications.
Prof. Wolfgang Haerdle, PhD
Top 1% globally cited statistician; expert in adaptive algorithms.
Hardware partners
We are seeking partners in sensing hardware to conduct a hackathon helping you:
- Turn commodity sensors into premium products
- Collaborate with DIU, AFRL, ONR, FUZE, DIU or similar
- Compete with fully-integrated defense primes
Data partners
We are open to data challenges do demonstrate the superiority of our aglorithm to you:
- 45% less errors on detecting UAVs from audio data
- 75.5% more accurate detection on radar data
- Multi-sensor fusion suitable
Research hubs
For NATO-aligned partner labs we offer:
- A completely new approach, originating from a long-forgotten branch of mathematics
- Suitable to detect UAV locations from cellphones and other civilian sensors
- Ignores accuracy VS SWaP trade-off. We do better on all dimensions
Let’s talk integration
Share your sensor modality, compute constraints, and deployment environment. We’ll propose a quick test plan.
Email:
philipp@phinorm.com
