About Pridatex

Pridatex is a Bay Area startup that developed a cutting-edge Differential Privacy software that completely preserves the quality of the original data.

Pridatex created a software that automatically anonymizes sensitive data, allowing businesses to share data with development teams and third parties in a legally compliant way. Furthermore, Pridatex allows employees to handle data without worrying about the legal and reputational repercussions in case of data breaches. Our technology is legally proven to strongly protect privacy through Differential Privacy.

Despite using Differential Privacy, our software shows the same linkable data at an individual level in order to preserve all discovery capabilities of the original data. It does so by obfuscating data instead of generating Synthetic Data or utilizing other heavy machine learning tasks. Thus, it can generate anonymous data that is at least 95% accurate in a small amount of time and with less computational resources, even with a small amount of data. As the datasets get larger, the anonymous data becomes more accurate. Thus, we can overcome the data utility restrictions that were previously imposed when utilizing these strongly complying methods. 

Supported by

Our Team

Arjun Banerjee
CEO & Co-founder

Researched on Data Privacy under a renowned professor and identified commercialization pain points. He developed the product with co-founder to address these pain points. He also works on the business and marketing strategy for the company, and thus acts as the bridge between the technical and the commercial sides of Pridatex.


Saibal Banerjee, Ph.D.
CTO & Co-founder

Has 30 years of machine learning, computer vision, and algorithms development experience in Silicon Valley industries. He has a Ph.D. in Computer Science, authored numerous publications, and has 15+ U.S. patents issued in his name. He has also created his own Networking startup during the latter half of the 2000’s.


Prof. Christopher W. Clifton
Academic Advisor

Is a renowned Purdue professor with 10 years of research and publication experience in Differential Privacy. He is contracted by the U.S. government to aid in the Census Bureau’s adoption of Differential Privacy. He is a valuable asset in guiding us to develop our solution with strong privacy protection guarantees.