Privacy-Preserving Technologies
Research into federated learning, homomorphic encryption, differential privacy and zero-knowledge proofs — privacy-preserving identity by construction.
Proving identity without revealing the underlying data.
Federated Learning
Models learn across silos without moving data.
Homomorphic Encryption
Compute on encrypted biometric templates.
Zero-Knowledge Proofs
Prove attributes without revealing them.
Differential Privacy
Protect individuals in aggregate analytics.
Real-world business use cases
How this technology delivers impact in government, fintech, and enterprise operations.
Federated Learning
Cross-silo model training without data sharing.
Encrypted Matching
Match biometrics without decrypting them.
ZKP Verification
Selective disclosure of identity attributes.
Differential Privacy
Protect individuals in analytics.
Sub-capabilities & technical set (8)
The granular technical stack executing beneath this domain.
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System standards reference
Industry certifications and regulatory frameworks validated for this technology domain.
Apply Privacy-Preserving Technologies to Your Stack
Collaborate with Mantra's engineering and research teams to deploy these technical capabilities inside your identity solution.