Research Institute

We actively engage with premier research institutions to architect systems that facilitate secure and private multi-party data and AI collaboration. Our focus is on developing frameworks that uphold data integrity and confidentiality while enabling productive joint ventures in analytics and machine learning.

Success stories

Our system is fortified with advanced techniques such as differential privacy, zero-knowledge proofs, secure multi-party computation, and federated learning. These innovations ensure robust security during data communication and safeguard the privacy of results. Our approach significantly enhances utility while curbing costs, all without compromising on privacy protection.

>10x

improvement on communication cost
improvement on model utility

>50x