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Technician adjusts a yellow robotic arm inside a glass-enclosed industrial workspace.

Physical AI Data Infrastructure

High-quality robotics data for
Physical AI

From data collection to annotation, quality control, and delivery, we build production-ready robotics datasets for foundation models.

Talk to usRequest a sample dataset
CAPTURE MODEEGOCENTRIC_RIG
DATA LAYERWORLD_CONTEXT
QC STATUSVERIFIED

OUR CAPABILITIES IN DATA

10,000+
Collection hours per month capacity
90%
quality pass rate on reviewed footage
20+
Task types captured
5+
Unique data modalities & environments

OUR PRODUCTS

Operator wearing an egocentric capture rig in a robotics laboratory.
01 / EGOCENTRIC DATA

Egocentric Data

Head-mounted, action-annotated data for imitation learning and robotic policies.

Learn More →
Engineer teleoperating a robot arm through a technical control interface.
02 / SIMULATION DATA

Synthetic Simulation Data

Domain-randomized synthetic data for faster training and sim-to-real transfer.

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Industrial robot arm inside a controlled simulation and validation environment.
03 / EGOCENTRIC HARDWARE

Egocentric Hardware

Industrial capture rigs for reliable, calibrated real-world data collection.

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PLATFORM ARCHITECTURE

The Robotics Data Engine

01

Data Collection

Capture high-quality demonstrations in real world environments using standardized collection protocols.

02

Data Understanding

Transform recordings into structured datasets with automated segmentation, metadata, and workflow intelligence.

03

Quality Control Engine

Multi-stage validation combines automated checks with expert review to ensure production grade quality.

04

Data Delivery

Production-ready datasets delivered in formats compatible with modern robotics and AI pipelines.

Operator wearing an egocentric capture rig collecting robotics training data.
Under the hood

Built for the pipelines that train modern robots.

Every recording is transformed into a synchronized, production-ready dataset with calibrated sensors, high-quality annotations, timestamps, metadata, and exports tailored to your training infrastructure. Compatible with NVIDIA Isaac Lab, Isaac Sim, custom perception stacks, and proprietary robotics workflows.

RGB+DepthAnnotationQuality ValidatedCustom schema

How a collection program works

01
DEFINE OBJECTIVE

Align on tasks, environments, sensors, and success criteria.

Week 1: 2–3 days

02
DESIGN RIG

Plan capture workflows, rigs, metadata, and quality standards.

Week 1: 3–5 days

03
COLLECT DATA

Capture diverse, high-quality demonstrations in real-world environments.

Weeks 2–3: 10,000+ hrs/month

04
PROCESS

Synchronize sensors, structure metadata, and prepare production-ready datasets.

Rolling: under 1 week

05
QA REVIEW

Validate accuracy through automated checks and expert review.

Rolling: under 1 week

06
ITERATE

Expand coverage, close data gaps, and improve dataset quality.

Continuous through cycle

07
DELIVERY

Production-ready datasets with annotations, metadata, and documentation.

Month close: 2–3 days

PRICING

Start with a sample. Scale with a custom program.

Begin with evaluation data, then move into task-specific collection once your schema is locked.

Sample Dataset
Free/evaluation

For teams reviewing quality, schema, and fit.

Request Sample →
  • - 10-15 hours curated clips
  • - Basic metadata
  • - Consent methodology
  • - Factory / retail coverage
  • - Evaluation use
Recommended
Pilot Collection
100-500h/paid pilot

For teams validating a workflow, task family, or collection schema.

Start Pilot →
  • - Buyer-defined task list
  • - Egocentric / exocentric capture
  • - Anonymization
  • - Basic annotation + QA report
  • - MP4 + JSON / CSV delivery
Enterprise Program
Custom/monthly

For ongoing model-training data programs.

Talk to Us →
  • - Dedicated capture ops
  • - Advanced annotation schema
  • - Monthly volume delivery
  • - HDF5 / CSV / custom formats
  • - Compliance documentation

Common questions, Answered

Can you deliver raw or fully annotated datasets?

Yes. We provide raw recordings, partially annotated datasets, or fully labeled data tailored to your training pipeline and annotation schema.

Which data formats do you support?

We deliver data in MP4, JSON, CSV, HDF5, and other custom formats required by your ML or robotics stack.

How do you ensure data quality?

Every dataset undergoes multi-stage QA, consistency validation, and manual review before delivery to ensure production-ready quality.

How do you protect confidential customer data?

All projects are handled under strict confidentiality agreements. Customer data is securely stored, access-controlled, and shared only with authorized personnel. Privacy requirements and retention policies are defined before collection begins.

Can you scale from pilot projects to large deployments?

Yes. Whether you require a few hundred hours for prototype validation or continuous monthly collection at scale, our workflows and infrastructure are designed to grow with your deployment.

TRANSMISSION OPEN _

Working on a physical AI system?

Tell us about your robot, your task, and where you're stuck on data. We'll respond within 48 hours and be direct about what we can build for you.

Currently piloting with early robotics teams.

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