TripleBlind Secures $ 24 Million for New Approach to Enterprise-Level Data Sharing and Preserves Privacy – TechCrunch

Organizations that have taken the leap into using big data to drive their businesses are increasingly looking for better and more efficient ways to share data with others without compromising privacy and data protection laws, which ushers in a rush of technologists who are creating a number of new approaches to fill this need. In the latest development, a startup called TripleBlind – who devised a way to encrypt data so that it can be shared without ever being decrypted or even leaving the data owner’s firewall, and keeping the whole process going. Compliant with data protection regulations – announces new funding following strong demand for its technology.

The Kansas City, Missouri-based startup closed a $ 24 million Series A funding round that it will use to continue to develop its technology and expand to a wider range of industry verticals. business. The cycle is co-led by General Catalyst and the Mayo Clinic, along with AVG Basecamp Fund, Accenture Ventures, Clocktower Technology Ventures, Dolby Family Ventures, Flyover Capital, KCRise Fund, NextGen Venture Partners and Wavemaker Three-Sixty Health. The round was oversubscribed but the company does not disclose its valuation. He has raised over $ 32 million to date.

TripleBlind’s platform, which officially launched in November 2020, now complies with privacy and data residency regulations in over 100 countries, including California’s HIPAA, GDPR, and CCPA. The company estimates that there are around 43 zetabytes of data stored by businesses around the world today that is not being used as it might be due to limitations imposed by both these and other rules. protection, as well as by the general reluctance to share intellectual property and other issues around data sharing. It works with data in a variety of formats including PII, PHI, genomic data, images, and confidential financial records.

As an indicator of where TripleBlind is finding initial traction for its product, Mayo – one of the world’s leading medical research institutions – is one of TripleBlind’s strategic investors. Mayo uses its technology both for data encryption and to help create algorithms based on datasets without the need to share raw data.

This solves a long-standing problem typically encountered when two institutions (or even one institution working with multiple datasets) collaborate: normally, they have to transfer data and / or algorithms based on that data, in order to form systems or conduct research.

With TripleBlind, the idea is that they don’t have to anymore. (The “triple” in its name refers to TripleBlind or a recipient data user who is variously “data blind, process blind, and result blind.”)

“Bringing together AI algorithms and data in a way that preserves privacy and intellectual property is one of the keys to delivering the next generation of digital medicine,” said John Halamka, MD, president of Mayo Clinic Platform. “These new privacy-protected solutions promise to usher in a new era of collaboration.” Halamka and Shail Jain, Global Managing Director, Data & AI at Accenture, both join as observers on this cycle’s board.

The Mayo Clinic also invested an undisclosed amount in an extension of TripleBlind’s $ 8.2 million funding round. Mayo Clinic is not its only strategic funder: Accenture and Okta are two others; other clients include Snowflake.

Riddhiman Das, co-founder and CEO of TripleBlind, said in an interview that healthcare and medical research continue to be important areas for TripleBlind, and that he is also seeing growing interest from financial services. , media and public services.

Innovations in big data analytics are opening new frontiers in how organizations can pool larger bodies of knowledge to help them make inroads and develop new algorithms in areas that have often been presented as figurative black holes, whether in medical research or forming an autonomous system, or tracking network activity for trends or malfunctions, or around better insight into customer sentiment, or the like thing.

The catch is that we are in an age where privacy and data protection are more important than ever, not only from a regulatory standpoint, but to our own tastes as consumers and, in the event companies, from an intellectual point of view. protection of property, so the liberal use of data comes with many caveats, even outright restrictions.

We are seeing an interesting proliferation of advanced technologies to address this paradox, including applications of homomorphic encryption, synthetic data sets, federated learning, and “blockchain” data putting, among others.

TripleBlind’s approach has been to create a system that it believes solves the various problems exposed by other approaches: for example, homomorphic encryption is resource intensive and difficult to scale; tokenization / masking / hashing and differential privacy reduce accuracy; synthetic data is not real real data; federated learning gives free rein to data reconstruction; and the blockchain is not configured for data sharing.

(On the other hand, and to much credit to much of the broader community of technologists working in this field, those working on specific solutions are in fact moving towards mixed approaches, borrowing elements different techniques, as a new generation approach, TripleBlind included.)

At TripleBlind, Das said he started thinking about trying a new approach to sharing data without compromising data protection or privacy when he previously worked at Alibaba’s Ant. The financial services giant had, in 2017, acquired eye scan biometrics startup EyeVerify for $ 100 million – where Das was the architect of the product – but the acquisition didn’t develop as Ant had hoped: it encountered controversy over privacy issues, or what Das described as “Data access problems”.

Specifically, “we struggled to access the data to improve our models and the accuracy of the service,” he said. He therefore went from there to the development of the company.

(In fact, Alibaba has never been able to come full circle, and now it looks like they are looking to divest the company, which has now been renamed the looser-sounding Zoloz.)

In his new role, Das said he’s starting to see a bigger picture emerge of how businesses, Ant in particular and others more generally, approach data and privacy issues. It covered more than biometrics.

“We also had problems accessing anti-money laundering data, knowing your customers’ algorithms, etc.,” he said. Data residency and privacy regulations “have really hampered our ability to use the data.”

He spent years evaluating different solutions and finally came up with the idea of ​​building something a little different to tackle the same problem: restrictions around contractual limitations. TripleBlind still applies encryption to data and algorithms, but its patented approach to encryption and the architecture of how data is used means that data never leaves its owner when used in calculations.

This is the critical point for investors.

“TripleBlind is an incredible platform for enabling businesses to collaborate on data while preserving privacy, data rights and intellectual property. Particularly important today in the healthcare industry, as the lack of data mobility results in fragmented and suboptimal care, ”said Quentin Clark, CEO of General Catalyst. “At General Catalyst, we believe that TripleBlind’s platform for enabling teams to work together with the most private and sensitive data is a necessary part of how businesses can be agile while respecting privacy. of their customers and the intellectual property of their partners. We are excited to be working with the TripleBlind team as they work towards achieving their mission. “

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