Data Infrastructure for Physical AI and Humanoids
Omnidirectional 3D capture, enriched annotation, and simulation-ready data to train the next generation of humanoid robots and embodied AI.
SABER
A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation. The first high-fidelity retail robotics action dataset built from natural human behavior.
PRISM
Unifying physical AI knowledge across space, physics, and embodied action. Fine-tunes NVIDIA Cosmos-Reason2 to state-of-the-art on physical AI benchmarks.
Real-world 3D data is the scarce apex of Physical AI.
Today’s robots are trained on internet 2D video, simulation, or narrow-field-of-view lab capture. Each leaves a gap. Our omnidirectional 3D platform captures the layer the others can’t reach.
Purpose-built for Physical AI training data.
A proprietary capture system, eight years of production hardening, and an end-to-end pipeline that turns real environments into simulation-ready training data.
Dual-Stream Capture
Synchronized 360° exocentric (Alia) + egocentric (GoPro) in a single pass. Complete spatial context — what the robot sees and how it appears in the scene.
CVPR-Pedigree Optics
Single-shot 360° stereoscopic design from IIIT Hyderabad, peer-reviewed at CVPR 2016. The optical breakthrough behind every dataset we ship.
8 Years in Production
Deployed across AMRs, surveillance, and smart city. Real-world failure modes already engineered out before the first humanoid dataset.
32+ Patents
A decade of protected optical IP. The capture platform is the moat — every downstream product inherits its quality.
From real-world capture to GR00T-ready training data, in one pipeline.
We don’t just sell a camera. We deliver real-world capture, annotation, 3D reconstruction, USD simulation export, and synthetic generation — as one infrastructure layer.
Capture
Synchronized Alia 360° + GoPro dual-stream in real environments
Annotate
AI-assisted (SAM2, Grounding DINO) + human QA — 10× faster
Reconstruct
3D Gaussian Splatting creates photorealistic scenes
Convert (USD)
Automated USD export with physics for Isaac Sim
Simulate
1,000+ frames/hour with domain randomization
Train
Validated on GR00T and Cosmos fine-tuning
Three ways to deploy Physical AI faster.
Datasets
Richly annotated grocery datasets — 500 hours each, up to 13 modalities per frame, dual-stream synchronized. Ready for LeRobot and Open X-Embodiment.
Browse datasets →Simulation Assets
Photorealistic digital-twin environments in USD format. 5 store environments, 2,000+ product assets with physics properties. Drop into Isaac Sim.
Browse the catalog →Custom Capture
Our team deploys to your facility with Alia rigs and the full annotation pipeline. Your data stays exclusively yours.
Talk to our team →Validated on NVIDIA’s Physical AI stack.
A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation. Fine-tunes NVIDIA GR00T N1.6 on dual-stream egocentric data to achieve 2.19× improvement over baselines in retail manipulation.
The first dataset to unify space, physics, and embodied action in a single real-world deployment domain. Fine-tunes NVIDIA Cosmos-Reason2-2B to state-of-the-art on physical AI benchmarks.
Building Physical AI? Let’s talk.
Whether you’re training humanoids, building world models, or deploying enterprise robotics — our data is built for your stack.