Over a Decade of Tokenization Innovation
Over a decade of innovation, engineering, and product development. An extensive patent portfolio. A singular mission: enable the secure use of sensitive data without compromising its value.
Organizations need to expand and accelerate the use of sensitive data while maintaining privacy, security, governance, and compliance. Traditional approaches often force a tradeoff between protecting data and preserving its analytical utility.
Anonos was built to eliminate that tradeoff.
Our technology enables governed, privacy-preserving data use through policy-controlled protection, controlled disclosure, and utility-preserving tokenization across analytics, AI, and enterprise workflows.
Data without the drama®
Anonos technology separates data value from identity without sacrificing governance, utility, accuracy, or speed. It does this by issuing different de-identifiers for different purposes, contexts, and time periods, with controlled re-linking.
Privacy isn't about hiding — it's about what companies can do with your data
Maggie Feys, Chief Strategist, Ethical Data Use — speaking at PrivSec London.
Show transcript
I'm Maggie Feys. I am Chief Strategist, Ethical Data Use with Anonos.
They have been stressing on — and that's okay — on security, but I think also the time now has come to see that data protection by design and by default must be there. So when we are innovative, we also have to be innovative when it comes down to privacy and data protection.
I don't have anything to hide, and I don't think that data protection or privacy is about what you want to hide or not want to hide. It's the fact of what companies — banks, for example, or ad-tech companies — can do with your data. If we don't get aware and don't push them into the fact that they have to be ethical about it, that can of course have some consequences. And I don't think everybody is that aware.
Our Principles
The principles that guide how we build, secure, and govern enterprise data systems.
Innovation
We challenge conventional assumptions about how sensitive data can be protected, governed, and utilized across AI, analytics, and enterprise systems.
Trust
We operate with transparency, accountability, and integrity in our technology, partnerships, and governance practices.
Utility
We believe privacy protections should preserve analytical value rather than destroy it.
Precision
We approach privacy, governance, and engineering with rigor, accuracy, and attention to detail.
Our History
Co-founders Ted Myerson and Gary LaFever spent more than a decade building enterprise data and risk-management systems before launching Anonos. Their previous company, FTEN, enabled securities broker-dealers and financial institutions to manage risk in real time, improving capital efficiency and regulatory compliance.
Following FTEN's acquisition by NASDAQ in 2010, the founders began developing a new approach to privacy-preserving data use focused on separating data utility from data sensitivity through dynamic de-identification, controlled relinking, and policy-driven protection.
Today, Anonos has built an extensive international patent portfolio and a platform designed to enable governed use of sensitive data across analytics, AI, and enterprise workflows.
By combining multiple privacy and data-protection techniques into a unified architecture, Anonos helps organizations reduce complexity, accelerate compliant data access, and preserve the utility of sensitive data at enterprise scale.
The future of data protection is utility-preserving, policy-controlled, and built for AI.
Where Enterprise Teams Build Governed Data Infrastructure
Anonos technology is designed collaboratively with enterprise partners, cloud providers, system integrators, and engineering teams responsible for deploying privacy-preserving data systems at scale.
Through technical workshops and implementation sessions, organizations work directly with Anonos to integrate governed, utility-preserving data protection into analytics, AI, and enterprise workflows.
The session pictured here brought together engineering and architecture teams from AWS, Yahoo, and Capgemini to explore implementation strategies for privacy-preserving analytics, controlled disclosure, and policy-driven data protection.
On the ground at industry events around the world
From packed conference halls to focused booth conversations, our team is out meeting the data leaders, engineers, and regulators shaping the future of privacy-preserving data use.
