We empower organizations to collaborate and innovate with data securely and responsibly

Diagram showing how the PryvX platform connects data collaborators, our products, and outcomes through privacy-enhancing technology

One platform for privacy-preserving collaboration

PryvX enables secure data collaboration through cutting-edge cryptography and a privacy-by-design solutions — connecting data providers and consumers so regulated sectors can collaborate on analytics without exposing raw data.

Computation on Encrypted Data

Run analytics and models directly on encrypted data — no raw data exchange between parties, ever.

Post-Quantum Cryptography

Fully Homomorphic Encryption and additive secret shares, built on cryptographic primitives designed to withstand next-generation threats.

Cloud-Agnostic Deployment

Deploy centralized or federated across AWS, GCP, Azure or on-prem — without re-architecting your existing stack.

No-Code AI & Analysis

Non-technical teams run privacy-preserving analysis and LLM-powered workflows on sensitive data without writing a line of code.

Core Technologies

FL

Federated Learning

Federated Learning is a machine learning technique that enables multi parties to train a model locally on its individual data, and share only the learnings to build a global model.

Use case

Joint fraud-detection or credit-risk models across banks and telcos without centralizing customer records.