We build Federated Learning Blocks
A native Web3 Data Privacy solution for Artificial Intelligence

Mission Statement

FLock.io enables decentralised and privacy-preserving machine learning. FLock.io uses Federated Learning to compute model parameters locally at data sources and uses Blockchain to coordinate machine learning governance between data sources. We envision a world where users do not have to trade privacy for functionality and the economic benefits of machine learning are not captured by any single party.
In a world where Machine Learning transforms every industry, its impact depends on how the value created is distributed and more broadly, who gets to decide on governance issues. Currently, the largest tech companies centralise data and computing their private cloud servers, leaving users little say on what data they provide or how they should be used.


We build a decentralised privacy-preserving solution for Artificial Intelligence. We proposed a research initiative called Federated Learning Blocks (in short, FLocks), which uses blockchain as a coordination platform among data holders to conduct Machine Learning while data stays local and private. By replacing the central entity that collects data and organises machine learning with blockchain, FLocks aims to empower users to mine insights from their own data and monetise at their own discretion.


FLock.io is founded by a group of Oxford alumni, ranging from post-docs & researchers in Privacy Computing and Machine Learning to industry pioneers in AI, Banking, and Consulting. The team is committed to FLock’s success, and is already self-funded with millions of USD to deliver product 1.0.

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