Enhanced Privacy
Process sensitive data while it remains encrypted, ensuring privacy throughout the entire ML lifecycle.
The problem
AI cannot train on data you are not allowed to expose
Healthcare and finance need models without handing plaintext to the processing environment.
Sensitive records must stay protected even while they are used. If training or inference decrypts the data, the model environment becomes another copy of the original risk.
Processing in the clear
Most ML pipelines decrypt before they compute.
Patient and financial records
Those datasets cannot leave a controlled boundary.
Model environment as a copy
Whoever runs training can see what the model saw.
Confidentiality during compute
Protection has to survive the operation, not just storage.
Security leadership
What the board is asking
Confidential AI & Machine Learning
Four questions surface in every security review.
What changes
Confidential computing for AI programmes
DuoKey's Confidential AI solution leverages Fully Homomorphic Encryption (FHE) to enable secure machine learning operations on encrypted data.
Advanced FHE
Distributed Key Management
GPU acceleration with NVIDIA
Confidential AI
Keep model training useful without surrendering the dataset
Proof in practice
Where teams deploy this
Related products
Confidential AI
Microsoft Double Key Encryption (DKE)
Keep Microsoft from unlocking regulated mail, files and Teams content alone, without leaving M365.
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