NeuralChain: Blockchain-Native Machine Learning
A decentralized machine learning framework that enables secure, privacy-preserving model training across distributed data sources without compromising data sovereignty.
Project Overview
NeuralChain bridges blockchain technology with machine learning to create a decentralized ecosystem where researchers and developers can train AI models across distributed data sources while maintaining strict privacy controls using zero-knowledge proofs and homomorphic encryption.
Python + Solidity + Rust
MIT + AI ethics addendum
v3.2.1 - 2025-10-01
Core Features
Decentralized Training
Execute machine learning training across distributed data sources without requiring data centralization.
Privacy Preservation
Uses advanced cryptographic techniques to protect sensitive data during model training.
AI Model Market
Create, share, and monetize AI models using a blockchain-based smart contract marketplace.
Real-World Applications
Federated Learning
Train AI models across multiple institutions while keeping sensitive data local to each organization.
Collaborative Research
Collaborate on global research projects without data silos using blockchain-based data governance.
Model Governance
Use smart contracts to enforce ethical AI training practices and transparent model auditing.
Data Monetization
Enable data providers to securely contribute data samples and earn tokens while retaining full control.
Join the NeuralChain Ecosystem
Help shape the future of decentralized machine learning frameworks and privacy-preserving AI research.