Your GPUs are
waiting on memory.
Inference at scale is bound by memory, not arithmetic. Morphics decides what moves across the memory hierarchy your servers already have, so accelerators spend their time computing instead of waiting.
We do not store. We do not move.
We decide what moves.
A chip stalled on a memory fetch is a chip not generating tokens.
An accelerator's economics are set by utilization: the fraction of time it spends computing rather than waiting. The provider that manages memory best has the most room to compete.
throughput against no caching at batch 1, on NVIDIA H100 80 GB.
over stock at batch 4 and 8, with the same cache size.
changes to your serving stack, models, endpoint or fleet topology.
Installs beside the accelerators you already own.
Why bandwidth belongs to the silicon, capacity belongs to the operator, and what the Morphics MMP decides in between.
How it worksA single-slot module alongside NVIDIA H100/H200 or AMD Instinct, available today, with a self-contained appliance planned.
See the productsMixture-of-experts on H100, against criteria registered before the runs. Output unchanged, and verified.
See the resultsOne third the price is nine times as likely to be routed to first. Utilization is margin, or price.
Try the simulatorOperators who have built hardware companies to the Fortune 500, backed by a team of twelve in AI, data science and silicon.
Meet the teamA couple of weeks of counters your engine already keeps, and a written answer on whether memory is costing you.
Talk to usFind out whether memory is costing your fleet.
The first step puts nothing in your request path: a couple of weeks of counters your serving engine already keeps, and a written answer. Then we confirm it on your own traffic, on your own hardware, against your current configuration.