Quantum-ready optimisation, on the hardware you already run

Encode

Your operational problem, which trucks, which faces, which order, under which constraints, is translated into a form the engine can solve. The modelling layer holds the real constraints of your operation: equipment behaviour, business rules, and failure modes, so the answer the engine returns is one you can actually run.

Solve

The engine searches the solution space in parallel, the way a physical system settles into a stable state. That is what makes it fast on hard combinatorial problems where conventional solvers slow down as the problem grows.

In mine planning, that produced a speedup of more than 1,000x over Google OR-Tools on a ten-year plan, with OR-Tools stopped unconverged at twelve hours. See /mining.

Deploy

It runs as a software block (C++ / Python) alongside your existing planning and dispatch tools. No redesign of your processes is required.

Why now

GPUs sat in machines for years before a software layer unlocked them for general compute and made the modern AI market possible. High-performance optimisation and control have stayed largely on CPUs. Hyphos brings that same class of acceleration to industrial optimisation.

What you need

Runs on commodity GPUs today, including a single consumer-grade laptop GPU; cloud GPU instances give the solver more headroom and a better result, so the deployment choice is yours rather than ours; the same encoding runs unchanged on quantum hardware as it matures.