for embodied AI.
Embodied AI teams are blocked by infrastructure, not ambition.
Push your policy. See every bottleneck.
Test to the limit, not the average.
Systematic perturbation across visual, semantic, behavioral, and physical axes. Surface the generalization boundaries no benchmark shows.
Compare models head-to-head.
Your policy vs RT-2-X, RT-1, or any baseline — strengths and gaps pinpointed across every evaluation axis.
Bottlenecks decomposed. Progress unlocked.
Every issue traced to root cause — bottleneck attribution across grounding, task reasoning, action execution, and world modeling. Know exactly where to focus next.
From policy to bottleneck report in one pipeline.
Push your policy. We match the rig.
Upload a checkpoint, container, or API endpoint. Matched to the right embodiment and environment — on our rigs or alongside yours.
Stress-test across the full ODD.
Combinatorial perturbation across 24 parameters — lighting spectra, surface reflectance, friction coefficients, object geometry, clutter density, camera pose, actuator latency, and more. Continuous runs, automated reset, 24/7.
Every bottleneck mapped. Iteration accelerated.
Root-cause decomposition across grounding, task reasoning, action execution, and world modeling. Performance boundaries across distribution shifts — know exactly where to focus next.
Brittleness Mapping
Find the exact ODD regions where performance degrades — the cliffs across generalization axes, not benchmark averages.
Scenario Flywheel
Every run generates reusable edge cases across perturbation factors. The more you test, the deeper the coverage compounds.
Bottleneck Attribution
Visual grounding, task reasoning, action execution, or world modeling — know where your next breakthrough is.
One rig. Infinite conditions.
Same physical setup. Thousands of unique test conditions. Our augmentation engine turns one environment into an entire distribution — so you test the ODD, not just the lab.
Built for teams pushing embodied AI forward.
Find in hours what used to take months.
Every checkpoint stress-tested across thousands of real-world variants. Bottlenecks surfaced and decomposed — so your next iteration is always the right one.
Your R&D budget goes to R&D. Not rigs.
Stop burning runway on eval infrastructure. Push your policy to our rigs and get depth of testing that would take 6 months to build internally. Accelerate progress from day one.
Same testbed. Every model. No excuses.
VLA, classical, and hybrid stacks under identical physical conditions. Reproducible, attributable, head-to-head — the way embodied AI research should work.
Infrastructure that compounds.
Internal Eval Rig
Kvasi
Find every bottleneck. Accelerate every iteration.
Stop rebuilding eval labs. Start making progress.