Privacy Enhancing technology platform and applications
Pryvx's privacy-preserving data collaboration platform offers cryptographic resource and innovative technologies.
Privacy-by-Design Collaboration
Collaborate across organizational and sector boundaries without sharing raw data. Computations happen on encrypted data, ensuring compliance with regulations.
Post Quantum cryptography
Uses post quantum cryptography such as fully homomorphic encryption scheme,
Federated and centralized architecture
Supports both federated (on prem setup) or centralized architecture.
No code interface
LLM integration for AI model building and data analysis, embracing no code intreface design.
PryvX's Privacy-Preserving Data Collaboration platform is designed to enable industries, such as telecom, financial services or other regulated industries to collaborate effectively to drive growth, reduce cost, risks, and prevent cyber crime.
PryvX platform takes advantage of advance cryptography and distributed machine learning under Privacy Enhancing Technology framework to enable collaboration without sacrificing data privacy.
Use cases
Telecom - Bank fraud prevention
Gather fraud intelligence between telcos and banks using privacy-preserving data collaboration — detect SIM fraud, mule accounts, and identity theft without sharing raw data.
Private Credit Scoring
Enable secure credit assessments by combining financial and alternative data sources through encrypted collaboration — empowering accurate scoring even for thin-file or new-to-credit users.
Threat Intelligence sharing
Through the use of multi-party computation engine organizations can jointly analyze, share and identify emerging threats without compromising the confidentiality of their individual threat data.
IoT security
Federated learning enables each IoT device to locally train a model within its specific environment, and share the learnings to a global model that improves the overall security posture without exposing individual device data.
BT Group collaborates with PryvX
Demoing a privacy enhancing platform at BT’s innovation showcase in Adastral Park, PryvX and BT are working together to help to combat cyber-crime and fraud in financial and telecom sectors.
What is 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.