Adaptive Learning

Federated Learning

Collaborative intelligence without data sharing. Train models across thousands of devices locally, sharing only the insights (gradients), not the raw data.

Decentralized Training

Model training happens on the edge—on your servers or devices. Your data never leaves your infrastructure.

Privacy First

Since raw data is never transmitted, compliance with GDPR, HIPAA, and CCPA is significantly simplified.

Global Model Aggregation

A central server aggregates the learned patterns from all nodes to create a superior global model that benefits everyone.

Bandwidth Efficient

Only lightweight model updates are transmitted, reducing network load compared to uploading terabytes of raw training data.

Global Model

Node 1

Node 2

Node 3

Node 4