The industry’s answer to AI demand is more GPUs, more data centers, more power, and more cooling. But not all GPU work is productive — and the gap has a name: structural compute waste.
The industry’s answer
More GPUs. More data centers. More power. More cooling. Each answer adds capital and operating cost — and each one still feeds workloads through the same leak: unnecessary computation, inefficient data movement, and low useful compute yield.
A different answer: the Vectris Control Plane
Vectris addresses the waste directly — audit, explain, control, recover — with a layer that is:
- Software-defined
- Infrastructure-level
- Deployed with no new GPU required
The economic outcome
More useful compute per GPU. Lower cost and energy per accepted token. More AI capacity from existing infrastructure — in software today, and along a path through runtimes, kernels, firmware, and silicon.
Vectris found productive capacity trapped inside the GPUs already deployed.
Adapted from a Vectris Labs infographic.