Unlock the full value of your GPUs with our Model-Defined GPU™ Optimization & Automation platform.
Stronger utilization. Lower energy per token. Better ROI.
A GPU can read 100% "busy" and still waste most of your money.
Busy = a kernel is loaded.
Productive = it's actually producing tokens at capacity.
Those aren't the same number. Most teams only ever see the first one.
Time-to-value is the new moat — In enterprise infra that used to be 6–18 months. Rapt does it in 30 days.
The pilot runs on your cluster: measure real utilization, deploy the model-aware layer, measure again, keep the ROI report. No hardware change.
32+ GPUs? Let's talk.
All month we asked one question: what's your real GPU utilization, and what's it costing you?
The ROI Calculator gives you the 5-minute answer — your real utilization, cost per token, and projected savings. No sales call, no demo, no change to your stack.
Most GPU decisions are guesses dressed up as data:
- Provision on what you think the model needs
- Trust the dashboard
- Add hardware when throughput stalls
Rapt observes what each model actually consumes — cores, SMs, memory, KV cache — then acts on it.
DeepSeek proved models can get radically more efficient. But an efficient model ≠ an efficient deployment — you can run the leanest model on infra that wastes 90% of the GPU under it.
With Rapt: 10× more DeepSeek-R1-Distill-Llama-8B INT8 models on one H100, 90%+ savings.