What’s Needed for Data Liquidity?

In our recent round table webinar with Okta’s Director, Corporate Counsel, Product and Privacy, Fatima Khan, Polsinelli’s Privacy Attorney, Liz Harding, and TripleBlind’s Co-Founder and CEO, Riddhiman Das, we covered the current state of privacy regulations and how enterprises are approaching private data sharing. Khan, Harding, and Das identified common themes around data collaboration, including:

  • Data localization and transfer restrictions
  • Data minimization 
  • Transparency 
  • Lawful Basis
  • Individual rights
  • Security

Not every law contains each theme, but it’s abundantly clear that these are the biggest hurdles for data sharing. There is a great concern for our society’s inability to enforce these regulations as well. Too often, enterprises rely on good faith that other parties involved won’t stray away from what’s agreed upon. Other parties could hold a copy of the raw data, run operations not approved by others, etc., and there’s no way of knowing. As a society, we are too technically advanced to leave our private, sensitive data in the hands of companies under little legal supervision.  

Transferring data from enterprise to enterprise has its challenges, and having to move data from one jurisdiction to another has historically been difficult and limits global data collaboration. Imagine the impact and growth we could have if we were able to share data from one country to another seamlessly?  

There are different policies between different countries, but there hasn’t been one solution to satisfy data residency regulations and laws everywhere. Other approaches like homomorphic encryption or secure enclaves haven’t been built to universally satisfy these laws. Ultimately, they fail to offer a solution that upholds individual rights, complies with the strictest regulations, requires little computational effort, and remains private and safe. 

TripleBlind was created to overcome these hurdles to data collaboration. TripleBlind’s solution is one-way encrypted and irreversible – meaning the data may never be reconstructed or re-identified. Via fine-grained permissions, TripleBlind ensures only authorized operations can occur, and works on any data or algorithm. It supports existing infrastructure with no specific hardware dependencies.

If it sounds too good to be true, reach out to us for a demo or free hands-on workshop at contact@tripleblind.ai. Read our Competing Solutions Blog Series if you’d like to learn more about TripleBlind’s superiority over other approaches like synthetic data.