Stateful Wave Computing

The optimizer that
settles first.

A measurement-efficient runtime that replaces the optimizer in your loop. When measurements are scarce or your device drifts, it reaches a usable answer in a fraction of the budget — watch it settle ahead of SPSA, live, below.

live convergence · weighted max-cut · n=24SWCSPSA
initializing run…
Where it wins

Built for the regimes where a classical optimizer stalls.

The runtime replaces gradient estimation with a residual-feedback update. That edge shows up in three places — and the client tells you honestly when you’re outside them.

01 / TIGHT BUDGET

Few shots, fast answer

Below the budget crossover it leads SPSA, parameter-shift, COBYLA and Adam on anytime quality.

02 / DRIFT

One measurement per round

Where gradient estimators can’t even run, it tracks a drifting target at the noise floor.

03 / LATENCY

Delay-bound loops

Its momentum acts as a predictive term, holding lock under control delay that breaks PI and PID.

Outside these — static problems at ample budget, hand-tuned PID control, coupled plants with no calibration — your current method is as good, and the runtime says so instead of overselling.
90-day evaluation

No fee. Your data. Your results.

Get a key, drop the client into your loop in one line, and run it on your own workload. The method runs on our endpoint — nothing lands on your disk.

Get your key →