/ 01 The thesis

The scarce resource in physical AI is no longer compute.

It's high-quality, legally usable data from the environments where robots must eventually operate. There are three ways to get it:

Criteria
Scraped web
Simulation
Dextod field
Rights-cleared for commercial training
✕
~
✓
True first-person contact & manipulation
✕
~
✓
Real-world exceptions & messiness
✕
✕
✓
Matches your deployment environment
✕
~
✓
Exclusive — competitors can't buy it
✕
✕
✓

/ 02 The platform

One platform. The entire data lifecycle.

P-01
Design
Program design
P-02
Onboard
Participants
P-03
Consent
Rights management
P-04
Deploy
Device fleet
P-05
Capture
Field operations
P-06
QA
Quality gates
P-07
Deliver
Secure delivery
P-08
Report
Performance

/ 03 The data

This is what you're buying.

Every episode ships training-ready.

Task phasesContact states6-DoF hand & head poseSemantic labelsLanguage descriptionsQA lineage

/ 04 Environments

Where robots must eventually operate.

ENV-01
Hospitality
GUEST SERVICE · ROOM TURNOVER · FRONT-OF-HOUSE
ENV-02
Foodservice
PREP · LINE WORK · PLATING · EXPO
ENV-03
Logistics
PICK · PACK · PALLETIZE · SORT
ENV-04
Industrial
ASSEMBLY · INSPECTION · MACHINE TENDING

/ 05 Trust

Consent is infrastructure.

Consented

Every participant informed, opted-in and compensated. No ambient scraping — ever.

Rights-cleared

Usage rights defined up front. Legally usable for training, evaluation and deployment.

Controlled

Environment-level permissions, quality gates and secure delivery on every dataset.

Built for frontier physical-AI developers

/ Mission

Build the trusted data layer between human work and machine intelligence.

For robotics & physical-AI teams

Build a Data Program

Egocentric and multimodal datasets, captured to your specification in the environments your models need.

For operators, venues & participants

Join the Collection Network

A controlled, compensated way to contribute your environment — with consent built in from day one.