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.

PUBLISHED · MAY 2026

SABER

A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation. A high-fidelity action dataset built from natural human behavior.

  • 44.8K samples
  • 100+ hours
  • 2.19X improvement

PUBLISHED · MARCH 2026

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.

  • 66.6% error reduction
  • 270K samples
  • 11.8M frames

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.

One pipeline. Real-world capture to VLA/VLM-ready training data.

We deliver real-world capture, annotation, 3D reconstruction, USD simulation export, and synthetic generation — as one infrastructure layer.

  1. Capture
    • Synchronized Alia 360° + GoPro dual-stream in real environments
  2. Annotate
    • AI-assisted (SAM2, Grounding DINO) + human QA — 10× faster
  3. Reconstruct
    • 3D Gaussian Splatting creates photorealistic scenes
  4. Convert (USD)
    • Automated USD export with physics for any USD-compatible simulator
  5. Simulate
    • 1,000+ frames/hour with domain randomization
  6. Train
    • Ready for VLA and VLM fine-tuning

Four ways to deploy Physical AI faster.

PRISM — VLM Datasets

Vision-Language datasets that unify space, physics, and embodied action.

SABER — VLA Datasets

Vision-Language-Action datasets on dual-stream egocentric data.

Simulation Assets

Photorealistic USD environments and product assets.

Custom Capture

Our team to your facility. Data stays yours.

Validated on leading Physical AI models.

SABER · Published May 2026
A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation. Fine-tunes NVIDIA GR00T N1.6 on dual-stream egocentric data to achieve 2.19X improvement over baselines in retail manipulation.

  • 2.19X Improvement
  • 44.8K Samples
  • 91% Fridge Success

PRISM · Published March 2026
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.

  • 66.6% Error reduction
  • 270K Samples
  • 5× Reasoning

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.