Privacy + Secure Machine Learning

Break the Data Barrier

Protect Privacy

Optimal k-Anonymity and Differential Privacy

Generate Insights

Decentralized Secure AI, ML

“The world’s most valuable resource is no longer oil, but data.”

– The Economist

Data privacy and Privacy regulations limit how much data a company can access for analysis

Every organization inevitably runs into the Data Barrier, the point at which valuable data is inaccessible due to risk of exposing sensitive information, risk of intellectual property loss, or regulatory constraints.

CryptoNumerics breaks the Data Barrier to generate better insights. This is achieved using a combination of Private Set Intersection, Differential Privacy, Optimal k-Anonymity, and federated or decentralized concurrent Secure Machine Learning.

Breaking through the Data Barrier

Financial Services

Investors work with data scientists to understand and attribute the performance and risk characteristics of their entire portfolio including their holdings in hedge funds.

Life Sciences

Researchers and data scientists increase the statistical significance and precision of their findings, ultimately advancing the development of new and improved therapies for cancer patients.

Social Good

Policy makers work with data scientists to develop better policies through increased understanding of issues in low-income areas for improved health outcomes and allocation of resources.

CryptoNumerics Team

We are a team of engineers and visionaries with previous experience in C-Level roles at Fortune 500 companies, in R&D roles at global organizations, and as founding teams of successful venture-backed start-ups.

Monica Holboke

Co-Founder & CEO/CSO

Ash Munshi

Co-Founder & Executive Chairman

Charles Marker


David Jensen

Head of Research

Peter Scholl

Cryptography Expert

Jimmy Fan

Co-Founder, Engineering

Roberto Cervantes

Co-Founder, Marketing

Hassan Bhatti

Co-Founder, Commercial