Security · Privacy-Preserving AI
Security and privacy, by construction
Decisions without exposing the data underneath. LuckMa layers privacy-enhancing technologies so the platform can compute on sensitive data without ever seeing it in the clear.
Privacy-enhancing technologies, layered
The privacy-preserving execution layer combines federated learning and differential privacy with confidential computing in trusted execution environments. Homomorphic encryption and secure multi-party computation — computing on data that stays encrypted — are on the roadmap, not yet live; a cryptography-literate reader should read those as planned, not shipped.
Encrypted before it leaves
Data is encrypted in transit and at rest, with selectable AWS/GCP regions for data residency. Processor terms, a data-processing agreement, and standard contractual clauses are part of the vendor due-diligence path for regulated buyers.
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See how this supports your DPIA, the platform architecture, and the technology underneath.