Royal Academy of Engineering
Advanced Nonlinear Technologies
Run models 25x larger than your hardware was designed for. Phone. Watch. Implant chip. No cloud required.
We built an AI architecture that compresses large models by 25–60x without losing quality. Same approach works across text, vision, genomics, protein, and generative AI. Validated across five modalities. Designed for analog hardware from day one.
7B-quality model in 750MB. Runs offline on smartphone, Apple Watch, ESP32. No cloud dependency. Full privacy.
26x less chip area than standard approaches. Maintains accuracy even at extreme analog precision levels. Zero reprogramming for domain switching. Fits 1.5B model on 7mm² chip.
Same architecture validated on language, vision, diffusion, DNA genomics, and protein sequences. Not five models - one approach.
Validated at circuit level with full physics simulation. Production-grade fidelity.
One base model serves hundreds of domain experts. Each specialist is tiny - swappable in milliseconds. Train a new one in minutes on a single GPU. The base model never changes.
Medical, legal, scientific, custom domains. 2ms switch time. 100 specialists on one GPU using less memory than a single standard model.
Freeze the base, train a tiny specialist layer. 8x improvement on math reasoning with 2.8% of parameters. Minutes, not days.
Your domain adapter stays on your device. The AI engine runs on our server. Neither side has enough to work without the other. Server keeps nothing.
Watch computes locally (280KB). Phone bundles the request (25MB). Server generates the answer (320MB). Adapter never leaves your device.
100 domain specialists on one GPU. Each customer's adapter is private. Switch in 2ms. $0.01/query instead of $10M/year for dedicated infrastructure.
Protein and DNA models on a laptop. Offline diagnostics on $50 devices. Pharmacogenomics at point of care. Your data never leaves your network.
Memory prices up 246%. HBM sold out through 2026. Our architecture needs 25x less. License for your GPU, cloud, device, or silicon.
Every store gets its own AI chatbot. 10MB per store. 1000 stores on one GPU. Private by architecture. Pennies per query.
Stage: Pre-Commercial
Architecture validated across 5 modalities. Models trained and benchmarked. Seeking design partners, pilot customers, and hardware collaborators.
Royal Academy of Engineering
We're looking for hardware partners, healthcare collaborators, and enterprise customers who need AI that runs anywhere.