Inpher believes that data privacy and security are fundamental to the future of data analysis and computing. That is why we developed a product and fine-tuned technology that allows for privacy compliant analysis on private data sources with zero exposure to the underlying data.
Inpher’s pioneering cryptographic Secret Computing technology powers advanced analytics and AI applications without exposing or transferring sensitive data across departments, organizations or jurisdictions.
Our core commercial solution, called the XOR Secret Computing Engine, is built off our proprietary advances in secure multiparty computation. Our Engine is based on secret sharing and Fourier approximation of real-valued functions that enable secure evaluation of functions across multiple private data sources. This technique allows for the maintenance of privacy without the tradeoff of precision and allows data analysts to run functions against single or multiple data sources without ever revealing the inputs.
AMLD EPFL 2022 / Program
Neural Concept
Neural Concept Shape (NCS) is the commercial and industrial implementation of a software package developed at EPFL’s computer vision laboratory over the last 4 years. NCS is the first Deep-Learning software specifically tailored for Computer Assisted Engineering application.
Booth #101