Advanced Nonlinear Technologies

7B intelligence.
750MB footprint.

Run models 25x larger than your hardware was designed for.
Phone. Watch. CPU. GPU. Implant chip.
No cloud required.

See the numbers Talk to us
25x
Larger model on same hardware
2 ms
Switch domain specialists
7 mm²
Entire AI on one chip
Technology

Bigger models, smaller everything.

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.

On-Device AI

7B-quality model in 750MB. Runs offline on smartphone, Apple Watch, ESP32. No cloud dependency. Full privacy.

Analog Hardware Native

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.

Five Modalities

Same architecture validated on language, vision, diffusion, DNA genomics, and protein sequences. Not five models - one approach.

Circuit-Level Validated

Validated at circuit level with full physics simulation. Production-grade fidelity.

Platform

One model. Unlimited specialists.

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.

Instant Specialists

Medical, legal, scientific, custom domains. 2ms switch time. 100 specialists on one GPU using less memory than a single standard model.

Built-In Fine-Tuning

Freeze the base, train a tiny specialist layer. 8x improvement on math reasoning with 2.8% of parameters. Minutes, not days.

Private by Design

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.

Three-Tier Architecture

Watch computes locally (280KB). Phone bundles the request (25MB). Server generates the answer (320MB). Adapter never leaves your device.

Applications

From cloud to clinic.

Results - numbers, not promises · Full benchmarks →
Language Compressed model matches full-size on standard reasoning benchmarks.
Vision Near-zero accuracy loss even at extreme analog precision. Beats standard digital.
DNA Beats significantly larger models on standardised genomic tasks. Trained on minimal data.
Protein Biologically valid sequences. Full amino acid diversity. No mode collapse. Orders of magnitude smaller.
Diffusion Comparable image quality at significant compression. Minimal quality trade-off.
Hardware Fraction of standard chip area. Dramatically less silicon. Full physics pipeline validated.
Serving Millisecond domain switching. Hundreds of specialists, one GPU. Instant, not minutes.

Stage: Pre-Commercial

Architecture validated across 5 modalities. Models trained and benchmarked. Seeking design partners, pilot customers, and hardware collaborators.

Backed by
Startup Program
Founders Hub
Inception
aiven Cluster
NatWest Accelerator

Building on-device AI?
Multi-tenant serving? Healthcare?

We're looking for hardware partners, healthcare collaborators, and enterprise customers who need AI that runs anywhere.