Federated Learning Engine Collaborative AI Without Compromise
Train ML models across decentralized data sources while maintaining complete data privacy
Core Capabilities
Secure Multi-Party Computation
Encrypted model updates with secure aggregation protocols
Edge AI Integration
On-device training with federated averaging
Differential Privacy
Noise injection mechanisms for enhanced privacy
Technical Architecture
Supported Frameworks
TensorFlow, PyTorch, ONNX
Encryption Standards
AES-256, Homomorphic Encryption
Compliance
GDPR, HIPAA, CCPA Ready