What's the difference between privacy-preserving AI-generated synthetic data and fake synthetic data? A definition to clear up confusion.

Privacy enhancing technologies are a vital part of modern data infrastructures. Learn what PETs are and how to select the right PET for the right use case!

A new type of privacy attack is emerging: using AI to re-identify people based on behavioral patterns. Old privacy tools no longer work, AI-generated synthetic data does.

Banks need to bridge the gap between data and innovation. The 15 most valuable synthetic data use cases in banking help financial data experts decide where to start.

Synthetic data is quickly becoming a critical tool for organizations to unlock the value of sensitive customer data while keeping the privacy of their customers protected and in compliance with data protection regulations such as GDPR and CCPA. It can be generated quickly in abundance and has been proven to drastically improve machine learning performance. […]

We've been talking to our friends in testing, brainpicking them to see where they need help the most.

The world is changing, and anonymous data is not anonymous anymore. Classic anonymization methods are no longer the fail-safe tools they once were. It's time to upgrade to synthetic data!

This is the second part of our blog post series on truly anonymous synthetic data. While Part I introduced the fundamental challenge of true anonymization, this part will detail the technical possibilities of establishing the privacy and thus safety of synthetic data.

In this two-part series, we are taking a look at how data privacy legislation evolved and explore how technology can keep up with the demands of regulation.