Encrypted Training
Train machine learning models on encrypted datasets without compromising data privacy or model accuracy.
Collaborative Learning Without Compromise
Traditional machine learning requires centralizing sensitive data for training—creating privacy risks, regulatory headaches, and competitive concerns. Encrypted Training changes the game.
Train powerful ML models on distributed, encrypted datasets from multiple organizations without anyone ever seeing the raw data. Enable true collaboration in healthcare, finance, and research while maintaining cryptographic privacy guarantees.
Key Capabilities
Everything you need for privacy-preserving ML training
Distributed Training
Train across multiple encrypted datasets from different organizations. Enable collaborative learning without data sharing or central aggregation.
Privacy-Preserving Gradients
All gradient updates happen on encrypted data. No intermediate values, activations, or weights are ever exposed in plaintext.
Differential Privacy
Optional differential privacy guarantees for additional protection against reconstruction attacks and membership inference.
Collaborative Medical Research
Multiple hospitals train diagnostic models on their patient data without sharing PHI. Each hospital's data stays encrypted and local, while everyone benefits from the collective knowledge. Perfect for rare disease research and improving diagnostic accuracy.
Cross-Border Financial Models
Financial institutions across different jurisdictions collaborate on fraud detection and risk models without moving sensitive data across borders. Meet data localization requirements while building powerful global models.
Federated Enterprise AI
Train models across multiple business units or subsidiaries without centralizing sensitive business data. Each unit maintains data sovereignty while contributing to company-wide AI capabilities.
How It Works
Encrypted training in four simple steps
Encrypt Datasets
Each participating organization encrypts their training data locally. Encryption keys never leave their infrastructure—they maintain full control.
Initialize Training Job
Define your model architecture, hyperparameters, and privacy budget. Our platform orchestrates distributed training across all encrypted datasets.
Encrypted Computation
Training happens on encrypted data using homomorphic encryption and secure multi-party computation. Gradients are computed and aggregated without decryption.
Export Encrypted Model
Receive a trained model that can be deployed for encrypted inference. All participants can verify the training process without seeing others' data.
Frequently Asked Questions
Common questions about encrypted training
READY TO BUILD?
Join the privacy revolution. Start building with Encrypted Training API today and experience the future of encrypted computing.