Federated Learning

A machine learning approach where models are trained across multiple decentralised devices or servers holding local data, without exchanging raw data, thus preserving data privacy.

Training AI across many devices without moving the data. Your phone can help improve a keyboard prediction AI using your typing patterns, but your actual messages never leave your phone.

Federated learning supports data sovereignty and privacy compliance by keeping data where it resides. For organisations operating across jurisdictions, it is a strategic approach that enables AI development without centralising sensitive data.