BASED IN san francisco,
CALIFORNIA
Available ALL AROUNd
worldwidE
Stereo Debth
+ Capture
Tokenomics
Tokenomics
Tokenomics
We’re building the first tokenized Physical Intelligence layer. Not just data, but the currency of dexterity. Mining the real world, not the Internet.
We’re building the first tokenized Physical Intelligence layer. Not just data, but the currency of dexterity. Mining the real world, not the Internet.
Title:
Component
% Allocation
Title:
Component
% Allocation
Title:
Component
Allocation
01
Genesis Mint
70%
01
Genesis Mint
70%
01
Genesis Mint
70%
02
Worker Data Rewards
20%
02
Worker Data Rewards
20%
02
Worker Data Rewards
20%
03
Treasury (LIQ, Ops)
10%
03
Treasury (LIQ, Ops)
10%
03
Treasury (LIQ, Ops)
10%
Human labor produces physical intelligence.
Human labor produces physical intelligence.
Human labor produces physical intelligence.
Physical intelligence generates revenue.
Revenue buys tokens to pay workers.
Higher-quality labor produces better intelligence.
Robotics revenue is recycled directly back to the humans teaching machines how to move.
Title:
Revenue Use
% Allocation
Title:
Revenue Use
% Allocation
Title:
Revenue Use
% Allocation
01
Token Buyback (Worker Pool)
35%
01
Token Buyback (Worker Pool)
35%
01
Token Buyback (Worker Pool)
35%
02
Platform Ops & Margin
45%
02
Platform Ops & Margin
45%
02
Platform Ops & Margin
45%
03
Expansion / R&D
20%
03
Expansion / R&D
20%
03
Expansion / R&D
20%
Workers are paid in upside, not just wages
They become long-term aligned contributors
This is tokenized labor with ownership.
The Data Flywheel
1. Workers Capture Data
A. 1440p egocentric video B. Real human dexterity
1. Workers Capture Data
A. 1440p egocentric video B. Real human dexterity
2. AI-Grade Datasets
A. Labeled, validated, B. Robotics-ready video
2. AI-Grade Datasets
A. Labeled, validated, B. Robotics-ready video
3. Enterprise Revenue
A. Robotics & AI companies B. License datasets (USD)
3. Enterprise Revenue
A. Robotics & AI companies B. License datasets (USD)
4. Revenue → Token
A. Fixed % of revenue B. Buys token on-market
4. Revenue → Token
A. Fixed % of revenue B. Buys token on-market
5. Token → Workers
A. Tokens paid to workers B. By data quality & volume
5. Token → Workers
A. Tokens paid to workers B. By data quality & volume
6. Incentive Alignment
A. Higher pay → better data B. Better data → more demand
6. Incentive Alignment
A. Higher pay → better data B. Better data → more demand