We build and deploy custom AI models, multi-modal sensor fusion, and compression pipelines on the drones, sensors, and field hardware you already run, delivered as focused engagements, not multi-year platforms.
CAGE 0M3Q5 · CMMC Level 1 · Colorado · Mohawk Valley, NY · Canada
Services
Four ways to work with us. Each one ships something you can run.
01
4–6 weeks
We take your sensor data and target hardware and answer one question: can a model do this job at the edge, at what accuracy, and at what power budget? You get a working prototype and a go/no-go report.
Scope and deliverables for Edge AI Feasibility Sprint →02
Custom detection, classification, or fusion models trained on your data, optimized for your SWaP envelope, and deployed to your platform with integration support (TAK, ROS, custom APIs).
Scope and deliverables for Model Build & Deploy →03
Already have a model? We shrink it with quantization, pruning, and semantic compression, so it runs on smaller hardware or sends less over a degraded link without losing what matters.
Scope and deliverables for Compression & SWaP Optimization →04
Independent evaluation of models, datasets, and hardware. Honest numbers on what performs, where the benchmark lies, and what to buy.
Scope and deliverables for Data & Benchmarking →Industries
ISR processing on unmanned systems, distributed C2 fusion, counter-UAS detection, operator monitoring. Engaged with US and Canadian defense programs; SBIR and IDEaS eligible; NDAA-compliant by design.
Defense & Dual-Use in detail →Real-time inference at remote sites with no reliable connectivity. Predictive detection on existing sensor networks, offline-first, on hardware that fits in a junction box.
Industrial & Energy in detail →Technology
Others build for the command post. We build for the last watt.
Our stack is built for the constraint everyone else designs around: no cloud, no bandwidth, no power to spare. Multi-modal sensor fusion turns separate feeds into one picture. Semantic compression sends meaning, not pixels. Neuromorphic processing runs always-on inference at a fraction of GPU power. Platform-agnostic, so it runs on what you already fly.
Explore the technology →Transformers vs. CNNs for RF-Based Counter-UAS Drone Detection
DOI 10.5281/zenodo.22847365
Gesture recognition, edge AI
ActiveDefense
Platform-agnostic edge AI that keeps C3BM operators informed when connectivity is denied.
ActiveDefense
EO/IR, RF, and acoustic feeds fused into one picture, on-board the platform.
CompletedResearch
Transformers vs. CNNs for detecting drones from RF, and a benchmark flaw that inflates accuracy.
Tell us the hardware, the sensors, and the constraint. We'll come back within a week with a scoped proposal.
Book a scoping call (opens in a new tab)