{ What Is AI-on-Chain }

A framework where AI models train, execute, and sync directly on blockchain

Designed for ML systems, Physical AI, and autonomous agents to operate in a shared, verifiable environment

Encrypted user data becomes reusable on-chain memory for continuous learning

{ Why It Matters }

{ 01 }

Physical AI learns from real-world
biometric and behavioral input

{ 02 }

Data collected by one AI system can
train another — across devices and companies

{ 03 }

On-chain profiles evolve with each
interaction and stay accessible via user consent

{ 04 }

Accelerates product iteration, model refinement,
and multi-vendor development

{ 05 }

Shared memory layer ensures no data is lost,
siloed, or duplicated

{ Use Cases }

Physical AI & Sensors

Smart rings, wearables, fitness trackers, edge devices

Stream pulse, motion, glucose, sleep, EEG directly to chain

ML & Robotics

Train on real-time, validated human input

Access continuous, structured datasets with full traceability

AI Agents

Train on real-time, validated human input

Sync agent behavior across devices and networks

{ Interfaces & SDK Access }

Annotate global datasets

Complete quests for rewards

Validate peer submissions

Boost your reputation

Deploy your own AI agents

Cover low-resource languages

Verify tasks via ZK proofs

Publish models to marketplace

Earn tokens for quality work

Join DAO governance

Run tasks from Telegram

Train models on real user data

Annotate global datasets

Complete quests for rewards

Validate peer submissions

Boost your reputation

Deploy your own AI agents

Cover low-resource languages

Verify tasks via ZK proofs

Publish models to marketplace

Earn tokens for quality work

Join DAO governance

Run tasks from Telegram

Train models on real user data

SDK Access

Inference

{ Run your Model }

Build AI workflows using verified, decentralized memory

Serve inference or sync data locally

Connect external models to on-chain data streams

{ The AI-on-Chain Era Begins }

ZoRo AI makes it possible to train and improve AI using encrypted, reusable, and permissioned data — creating a shared foundation for intelligent systems, Physical AI, and robotics.