We build systems that make
AI cheaper, faster, and smarter.

PRL3 is a kernel-level inference governance layer that sits between your application and your LLM provider. It learns which queries repeat, routes them through a verified semantic cache, and physically blocks GPU access until a valid request arrives. The result: dramatically fewer API calls, lower energy consumption, and full auditability — without changing your existing stack.

KANACKI is a symbolic regression system that recovers exact mathematical expressions from data — including physical laws, engineering relationships, and noisy real-world signals. Achieved perfect scores on the Feynman benchmark (100/100) and Nguyen benchmark (12/12), including noise-corrupted variants. Published open-access on Zenodo under CC BY 4.0.

First demonstration of passive rule extraction on a real quantum processor. The system learns process behaviour — Bell states, GHZ patterns — without disturbing the computation. Foundation for efficient quantum characterisation and future quantum governance layers.