PVML

Overview

PVML is designed to address the critical need for data privacy and security in the era of AI and data-driven insights. It provides a privacy-preserving database solution that allows organizations to perform collaborative data analysis and train machine learning models directly on encrypted or sensitive data, without requiring the data to be decrypted or shared in its raw form.

The platform leverages advanced cryptographic techniques, such as homomorphic encryption and differential privacy, to ensure that computations can be performed securely on data while preserving its confidentiality. This enables use cases like secure data sharing between different parties, federated learning across distributed datasets, and compliant AI development on sensitive information (e.g., healthcare, finance) where regulations prohibit direct data pooling. PVML aims to unlock the value of siloed or restricted data, fostering collaboration and innovation while maintaining the highest standards of privacy and compliance.

Key Features

• Privacy-Preserving Database
• Secure Collaborative Analytics
• Confidential AI/ML Training
• Support for Sensitive Data (Healthcare, Finance, etc.)
• Compliance with Data Regulations (GDPR, HIPAA, etc.)
• Advanced Cryptographic Techniques (Homomorphic Encryption, Differential Privacy)
• Scalable and Performant Data Operations

Supported Platforms

• Web Browser
• API Access