HARDWARE-AWARE EXECUTION DESIGN
Make your AI
keep up.
Faster models.
Faster robot workflows.
We redesign the execution.
You get the optimized build, compiler and runtime.
FIRST PoC FREE · ~2 DAYS / MODEL AFTER SETUP
faster
query-to-tracking
Measurement scope
Recorded VLM + segmentation query-to-tracking lock on Jetson Thor: 3.16 to 0.30 seconds, a 10.5× ratio. This is a selected pipeline response comparison, not a matched p50 inference benchmark.
BEYOND A SINGLE MODEL
Faster inference.
Faster missions.
faster first delivery
Serving-robot simulation · AGX Orin
inference optimization alone
Inside this comparison
First delivery in the recorded serving-robot simulation. All three paths use Cosmos-Reason2-2B, GR00T N1.6 and gear_wbc on Jetson AGX Orin. The Execution Design path combines inference optimization with the demonstrated orchestration. These are selected recorded runs, not a real-world fleet benchmark or an isolated orchestration ablation. The source video also shows separate scenarios and explicitly projected output.
MEASURED ON THE HARDWARE
Pick your board.
See the difference.
Point cloud. Stereo depth.
Same-board before / after.
Speed preset · Reported benchmark latency
Recorded run: 451 → 27 ms. Rounded timings appear in the video.
What is measured
Sonata (PTv3) with a ScanNet-20 head, fastest preset. Each ratio compares the stated baseline and optimized configuration on the same board. Thor uses 451 ms stock; AGX Orin and Orin Nano use the supplied FP32 references. Full-sample / request timing follows the board's benchmark harness. These are workload latency measurements, not camera-to-action latency or robot control rates. Presets trade speed against task quality; numbers are not a cross-board ranking.
WHAT YOUR TEAM GETS
The performance.
And the software to run it.
Your model. Your target.
A build your team can integrate.
EXECUTION DESIGN
Model to metal.
Designed for the model, workload and board.
for your team.
Optimized build
Integration interface
Reproducible comparison
Explore the engineeringVisual walkthroughs+
From model
to silicon.
Graph. Memory. Kernel. Runtime.
Full policy. 61% less latency.
One expert step: 16 layers in one persistent kernel. Composed research build.
Benchmark conditions
Warm full-policy call on one fixed task-0 raw observation, batch 1, 10 Euler steps. The measured harness includes preprocessing, tokenization, noise, transfers, postprocessing and synchronization; model loading and disk reads are excluded. Four rounds of 20 warmups and 100 measured calls. This is a composed research build, with integration review still open. The complete gain is not attributed to the persistent kernel alone. Memory and graph examples above are structural changes and do not imply a separate whole-model speedup.
Customers
Technology ecosystem
Programs & community
YOUR FIRST OPTIMIZED BUILD
Your model.
Next.
Start with one model and one target board.
Build this for our teamAfter setup and scope agreement.
Model or config
Target hardware
Performance goals
A runnable build.
Measured before / after.
Setup and scope
Typical setup takes 3 hours to 1 day. Approximately two days per model covers optimization and validation after the supported target, inputs and evaluation are agreed. A configuration can be used to benchmark the closest suitable model. Full-system integration and production acceptance are scoped separately.