About Antelligent
It's a consequence of building on the wrong architecture. We're fixing that.
Vision
"Intelligence should be able to go anywhere a human goes."
A doctor in a rural clinic. A soldier in the field. A device with no signal. A regulated system that can never touch a third-party server. These are not fringe use cases — they're billions of people and some of the most consequential decisions humanity makes.
Our vision: a society of tiny, specialised models — orchestrated and local — running everywhere a human goes.
Mission
"To accelerate the world's transition to sustainable AI."
Sustainable as in requiring dramatically fewer resources — making it cost-effective and environment-friendly. The average AI inference is 99% wasted compute. We're building the architecture that eliminates that waste.
Our story
Advanced Nonlinear Technologies was founded on a single insight: the reason AI can't follow humans into the places they go most isn't a resource problem — it's an architecture problem. Every major AI system today is designed to run in the cloud, on hardware the size of a server room, consuming megawatts of power. That's not sustainable, and it's not universal.
Our proprietary compression technology compresses large models by 25–60% with measured quality retained. That's not quantisation or pruning — it's a fundamental rethinking of how neural network weights encode information, validated across language, vision, genomics, protein sequences, and generative AI.
The result: specialised, production-grade models — from 10–100M-parameter task specialists to a language model that fits in 750 MB and runs offline on a smartphone. A hundred domain specialists that share a single GPU, switching in 2 milliseconds. Compute-in-memory silicon, in development — the substrate that lets a society of tiny models run for years on a coin cell.
We're headquartered in London and supported by Google for Startups, Microsoft Founders Hub, NVIDIA Inception, and AWS Activate. Our Everyday Series platform is already in production with paying customers, and our compute-in-memory silicon is still pre-commercial. We're actively seeking design partners, pilot customers, and hardware collaborators.
Supported by
We're looking for hardware partners, enterprise customers, and researchers who share our conviction that AI should be sustainable and universal.