TripleBlind Lands $24 Million in Series A Funding Led by General Catalyst and Mayo Clinic, in an Oversubscribed Round

  • Enables Enterprises to Unlock and Commercialize enormous amount of Unused Data*
  • Mayo Clinic Joins Round as Strategic Investor, Expands Equity Position
  • Demonstrates Accelerated Market Interest in Comprehensive Data Privacy Solutions     
  • Accenture and Mayo Add Board Observers

 

KANSAS CITY, MO – October 18, 2021 – TripleBlind, the private data sharing company that offers proprietary cryptographically-enforced data privacy solution, announced today it has received $24 million in an oversubscribed Series A funding led by General Catalyst and Mayo Clinic. This round follows TripleBlind’s pre-seed raise of $8.2 million announced in March 2021.

TripleBlind’s solution enables entities to share and collaborate with data anywhere in the world. without the need to share raw data, thus preserving privacy and security while meeting regulatory standards, (including with data while enforcing the data privacy and data residency regulations now in place in more than 100 countries, including HIPAA and GDPR, as well as similar regulations in four U.S. states, such as and California’s CCPA).. 

“When we launched last November, the primary interest in TripleBlind’s solution was among healthcare organizations, to more effectively share data while enforcing HIPAA and GDPR,” said Riddhiman Das, TripleBlind’s Co-founder and CEO. “Today, interest has grown exponentially and now includes leaders in financial services, media and telecommunications, energy and many other industries where sharing data assets is critical to sustained, long-term growth. The strong interest from our current and new investors highlights the growing market need for data privacy solutions that are both effective and efficient.”

“TripleBlind is an incredible platform for empowering companies 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 non-optimal care,” said Quentin Clark, Managing Director, 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 companies will be able have agility while respecting the privacy of their customers, and the intellectual property of their partners.  We are thrilled to work with the TripleBlind team as they work to achieve their mission.”

“Bringing together AI algorithms and data in ways that preserve privacy and intellectual property is one of the keys to delivering the next generation of digital medicine,” says John Halamka, M.D., President of Mayo Clinic Platform, who joins the TripleBlind Board as an observer. “These novel privacy-protected solutions promise to usher a new era of collaboration.”

In addition to General Catalyst and Mayo Clinic, Series A round participants include AVG Basecamp Fund, Accenture Ventures, Clocktower Technology Ventures, Dolby Family Ventures, Flyover Capital, KCRise Fund, NextGen Venture Partners, and Wavemaker Three-Sixty Health.

 

About TripleBlind

TripleBlind offers proprietary cryptographically-enforced privacy for data and algorithms, allowing institutions to collaborate around the most private and sensitive data without it ever being decrypted or leaving their firewall. TripleBlind Keeps data private and in place while allowing authorized operations on any type of data, any algorithm, computable by third parties in real-time. TripleBlind does not host or access the data.  TripleBlind Two min Overview Video

The TripleBlind Private Data Sharing Solution unlocks the estimated 43ZB of data stored by enterprises today that are inaccessible and not commercialized due to privacy concerns, operational complexity and regulations. The company’s patented breakthroughs in advanced mathematics enable organizations to secure larger and more diverse data sets for innovating enhanced algorithms for medical diagnoses and improved anti-fraud initiatives in financial services. It is the only technology that enables enterprises to rapidly commercialize data while maintaining compute performance; enabling analysis of all data types, such as PII, PHI, genomic data, images, and confidential financial records; and enforcing  complying all international and regional data privacy standards, including HIPAA, GDPR, PDPR, and CCPA.

TripleBlind technology significantly differs from existing solutions and is not based on homomorphic encryption, secure enclaves, tokenization/masking/hashing and differential privacy, synthetic data, federated learning and blockchain. Refer to competing solutions section on our website. For an overview, a live demo, or a one-hour hands-on workshop, contact@tripleblind.ai.

 

About General Catalyst
General Catalyst is a venture capital firm that invests in powerful, positive change that endures — for our entrepreneurs, our investors, our people, and society.  We support founders with a long-term view who challenge the status quo, partnering with them from seed to growth stage and beyond to build companies that withstand the test of time. With offices in San Francisco, Palo Alto, New York City, London, and Boston, the firm has helped support the growth of businesses such as: Airbnb, Deliveroo, Guild, Gusto, Hubspot, Illumio, Lemonade, Livongo, Oscar, Samsara, Snap, Stripe, and Warby Parker. For more: www.generalcatalyst.com.

 

Contact
Victoria Guimarin
UPRAISE Marketing + Public Relations for TripleBlind
tripleblind@upraisepr.com
415.397.7600

TripleBlind to Highlight Benefits of Enhanced Data Sharing and Collaboration in Healthcare and Fintech at Upcoming Industry Events

KANSAS CITY, MO., Oct. 15, 2021 – Thought leaders from TripleBlind, the solution that enables entities to collaborate without the need to share raw data and without that data ever leaving the company’s firewall, will present at several upcoming industry events. 

At events focused on healthcare and fintech, TripleBlind will speak on compliance when sharing data across international borders and throughout all industries and data platform enablement.

TripleBlind will participate in these upcoming events:

  • HLTH 2021, Oct. 17-20, held at the Boston Convention & Exhibition Center in Boston. TripleBlind co-founder and CEO Riddhiman Das will present on the topic, Data platform enablement in the age of privacy, on Tuesday, Oct. 19 from 4:45-4:55 p.m. ET.

Das’ session will give insight into how advanced privacy-enabled data-sharing technologies, such as TripleBlind’s solution, can greatly enhance scientific collaboration between groups and allow for more rapid development and scalable implementation of AI-driven tools to advance healthcare.

TripleBlind will exhibit at booth #627. To schedule a meeting with TripleBlind during HLTH, reach out to mitchell@tripleblind.ai. Click here to register today, and use code “21HLTH_tripleblind150” to save $150.

  • Money 20/20 U.S., Oct. 24-27, held at The Venetian Resort in Las Vegas. Das will present Five Data Privacy Predictions for 2022 and Beyond alongside Liz Harding, privacy expert and Shareholder at Polsinelli, and Sanjib Kalita, CEO of Guppy. The session will take place Monday, Oct. 25, from 9:55-10:25 a.m. PT at Serendipity Stage, Expo Hall, Level 2.

The rapid increase in the global market for big data and business analytics, projected to reach more than $500 billion by 2026, has created complex privacy and security issues in the fintech space. In this discussion, Das, Harding and Kalita will give insight into data privacy predictions to expect in the next year and how they will affect the financial industry, including the benefits of sharing data and not keeping it locked in a silo.

Click here to register.

 

About TripleBlind

The TripleBlind Private Data Sharing Solution unlocks the estimated 43ZB of data stored by enterprises today that are inaccessible and not commercialized due to privacy concerns, operational complexity and regulations. The company’s patented breakthroughs in advanced mathematics enable organizations to secure larger and more diverse data sets for innovating enhanced algorithms for medical diagnoses and improved anti-fraud initiatives in financial services. It is the only technology that enables enterprises to rapidly commercialize data while maintaining compute performance; enabling analysis of all data types, such as PII, PHI, genomic data, images, and confidential financial records; and enforcing all international and regional data privacy standards, including HIPAA, GDPR, PDPR and CCPA.

TripleBlind is superior to existing solutions such as homomorphic encryption (slows compute performance), secure enclaves (siloes data), tokenization/masking/hashing and differential privacy (reduces accuracy), synthetic data (not real data), federated learning (no protections against data reconstruction) and blockchain (does not enable data sharing). Innovators including Accenture, Mayo Clinic, and Snowflake trust TripleBlind to protect sensitive data. For an overview, a live demo or a one-hour hands on workshop, contact@tripleblind.ai

 

Contact

Victoria Guimarin
UPRAISE Marketing + Public Relations for TripleBlind
tripleblind@upraisepr.com
415.397.7600

As The World Rapidly Creates Data, TripleBlind’s Solution Offers Enterprises The Ability To Share Data Across Borders and Industries

During the last five years, the amount of data produced around the world has multiplied quickly. Analysts at IDC predict that by 2025, global data usage will reach an astounding 163 zettabytes. Enterprises have needed to quickly find ways to harness this data for business, enrichment and analytics benefits.

Mass amounts of data have made breaches and personal identity compromises a common occurrence, compelling business and healthcare entities to adopt their own version of regulations surrounding data collaboration, like HIPAA. Additionally, more countries and states around the world are creating separate, geo-based data privacy regulations. This year, in the United States alone, two states signed new data privacy regulations into law and seven others introduced pending privacy laws. Internationally, Brazil’s first comprehensive data protection regulation became enforceable August 2021 and China’s Personal Information Protection Law will enter into force in November 2021.

Companies are now required to ensure cybersecurity aspects of stored data, and compliance and governance surrounding data sharing. The pace of technology and its advancements is fast, but the regulatory and legislative process is slow, making it difficult for enterprises to ensure they are always collaborating compliantly.

TripleBlind’s CEO, Riddhiman Das, recently spoke with Jerry Buckley, a founding partner of Buckley LLP, and Jody Westby, a prominent data security consultant, for the ADCG Podcast to discuss the rapid evolution of data management and data governance. 

Das suggests that U.S. regulators can more accurately keep up with the rapid change in data worldwide by creating a simplified, overarching federal regulation for data collaboration. 

“Today enterprises are facing a hodgepodge of state privacy regulation, the main specific privacy regulation, and those often don’t have a lot of overlap. That is a significant hindrance to data liquidity,” said Das. “If data is the new oil, it is not flowing because of the inability to have clarity on how to make the data liquid.”

 

TripleBlind’s solution makes it possible for enterprises to share data collaboratively while ensuring they remain compliant with every data privacy regulation across borders and industries. TripleBlind is the only mathematically proven, privacy-first and privacy-centric approach to collaboration. Data can never be re-identified once it is shared and can only be used for its intended purpose.

Any data privacy regulation can be laid on top of TripleBlind, and it will act as the digital rights and rules of the data trade. This approach ensures that data remains private, but can also only be used for operations that are compliant with whatever regulations are in place for the transaction. 

The previous expectation for companies was to “not be evil” when it comes to data sharing. By eliminating any possibility for data misuse, companies “can’t be evil” when collaborating through TripleBlind. TripleBlind unlocks the possibility for enterprises to remain safer and more compliant than they would be if they were collaborating through various competing solutions for data sharing.

To listen to the full ADCG Podcast episode featuring Das, please visit HERE.

If you’re interested in learning more about how TripleBlind can help you unlock compliant data sharing across borders and enterprises, schedule a call or demo at contact@tripleblind.ai.

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.

Money20/20 USA, October 24-27, 2021, Venetian Resort, Las Vegas

At Money20/20 USA, TripleBlind Co-Founder and CEO Riddhiman Das will lead a panel on the topic “Five Data Privacy Predictions for 2022 and Beyond.” Panelists will include Sanjib Kalita, Editor-in-Chief of Money20/20 and Elizabeth Harding, Attorney at Polsinelli LLP. Click here to learn more about the event, here to set up a meeting or demo with TripleBlind.

IAPP Privacy. Security. Risk., October 21-22, 2021, San Diego

Check back soon to learn when Co-founder and CEO Riddhiman Das will speak and his topic. Click here to set up a meeting or demo with TripleBlind

HLTH, October 17-20, 2021, BCEC Boston

The TripleBlind team will exhibit at HLTH 2021 in Boston, so swing by booth 627 to say “hi”. Learn more about HLTH here, click here to set up a meeting or demo with TripleBlind.

TripleBlind Named a “Think Outside The Box” Solution for Moving Digital Medicine Forward

We were excited to see TripleBlind was included with other “Think outside the box” solutions in an article by John Halamka, M.D., president of Mayo Clinic Platform. The full article explores how data can be compliantly exchanged through TripleBlind’s cryptographic approach, and how once shared via TripleBlind’s one-way encryption, healthcare information remains private and cannot be reconstructed. 

As a thought leader surrounding all things pertaining to sharing healthcare data, John notes that TripleBlind “allows Mayo Clinic to test its algorithms using another organization’s data without either party losing control of its assets.” 

We agree with John 100% that the “magic” is “always about the math,” which is why TripleBlind’s solution has been mathematically tested and proven to keep data private. This market differentiator is a good example of why TripleBlind’s market traction is accelerating.

Check out an excerpt from John’s full article below, and read the full article here: https://bit.ly/3nDabNh 

 

Secure Computing Enclaves Move Digital Medicine Forward

At Mayo Clinic Platform, we are deploying TripleBlind’s services to facilitate sharing data with our many external partners. It allows Mayo Clinic to test its algorithms using another organization’s data without either party losing control of its assets. Similarly, we can test an algorithm from one of our academic or commercial partners with Mayo Clinic data, or test an outside organization’s data with another outside organization’s data.

How is this “magic” performed? Of course, it’s always about the math. TripleBlind allows the use of distributed data that is accessed but never moved or revealed; it always remains one-way encrypted with no decryption possible. TripleBlind’s novel cryptographic approaches can operate on any type of data (structured or unstructured images, text, voice, video), and perform any operation, including training of and inferring from AI and ML algorithms. An organization’s data remains fully encrypted throughout the transaction, which means that a third party never sees the raw data because it is stored behind the data owner organization’s firewall. In fact, there is no decryption key available, ever. When two health care organizations partner to share data, for instance, TripleBlind software de-identifies their data via one-way encryption; then, both partners access each other’s one-way encrypted data through an Application Programming Interface (API). That means each partner can use the other’s data for training an algorithm, for example, which in turn allows them to generate a more generalizable, less biased algorithm. During a recent conversation with Riddhiman Das, CEO for TripleBlind, he explained:

“To build robust algorithms, you want to be able to access diverse training data so that your model is accurate and can generalize to many types of data. Historically, health care organizations have had to send their data to one another to accomplish this goal, which creates unacceptable risks. TripleBlind performs one-way encryption from both interacting organizations, and because there is no decryption possible, you cannot reconstruct the data. In addition, the data can only be used by an algorithm for the specific purpose spelled out in the business agreement.”

TripleBlind COO Greg Storm to Participate in Think Tank of Industry Leaders at Money20/20 Europe, Sept. 21

WHO:

Greg Storm, Co-founder and COO, TripleBlind
Dave Birch, Global Ambassador, Consult Hyperion
Louise Maynard Atem, Research Lead, Women in Identity
Emma Lindley, Co-Founder, Women in Identity
Felix Gerlach, CPO & Co-Founder, Passbase
Katryna Dow, CEO and Founder, Meeco

WHAT:

On September 21, TripleBlind’s COO, Greg Storm will participate in a Think Tank at Money20/20 Europe based on the topic “The future is trustless. What do we need instead?” Storm will join other industry experts to discuss whether trust is an outdated concept or not, and how enterprises can trade and share data without trust.

WHY:

If data is the new oil, it is not flowing correctly due to risks of unauthorized use, regulation, and compliance concerns. Unlocking private data sharing will lead to advancements in identity protection, fraud management, macroeconomic insights, and more in fintech.

TripleBlind provides zero-trust data sharing that allows enterprises or third parties to analyze and use data without ever seeing it or duplicating it.

WHEN:

Tuesday, September 21, 2021
Money20/20 Europe, Amsterdam
4:00 – 5:00 p.m. CEST

WHERE:

Participants can register for Money20/20 here.

MEDIA:

Storm will be available for pre-event interviews, as well as interviews on-site at Money20/20. To coordinate, please email tripleblind@upraisepr.com.

About TripleBlind

TripleBlind unlocks the estimated 105 petabytes of data stored by enterprises today that are inaccessible and not commercialized due to privacy concerns, operational complexity and regulations. The company’s patented breakthroughs in advanced mathematics enable organizations to secure larger and more diverse data sets for innovating enhanced algorithms for medical diagnoses and improved anti-fraud initiatives in financial services. It is the only technology that enables enterprises to rapidly commercialize data while maintaining compute performance; enabling analysis of all data types, such as PII, PHI, genomic data, images, and confidential financial records; and enforcing all international and regional data privacy standards including HIPAA, GDPR, PDPR and CCPA.

TripleBlind is superior to existing solutions such as homomorphic encryption (slows compute performance), secure enclaves (siloes data), tokenization/masking/hashing and differential privacy (reduces accuracy), synthetic data (not real data), federated learning (limited use for algorithms), confidential computing (requires data centralization) and blockchain (not interoperable). Innovators including Accenture, the Mayo Clinic, and Snowflake trust TripleBlind to protect sensitive data. For an overview, a live demo or a one-hour hands on workshop, contact@tripleblind.ai.

 

TripleBlind Contact:

Victoria Guimarin
UPRAISE Marketing + PR for TripleBlind
tripleblind@upraisepr.com
510.331.9548

 

Kamyar Naficy
KNECTCOMMS for TripleBlind
kn@knectcomms.com
+44(0)7453 323 367

 

How TripleBlind’s Data Privacy Solution Compares to Differential Privacy

Differential privacy is not a specific process like de-identification, but a property that a process can have. For example, it is possible to prove that a specific algorithm “satisfies” differential privacy. Informally, differential privacy guarantees the following for each individual who contributes data for analysis: the output of a differentially private analysis will be roughly the same, whether or not you contribute your data.

When computing on data via differential privacy, it adds stochastic deterministic noise to each data element that masks the actual data element. Stochastic refers to a variable process where the outcome involves some randomness and has some uncertainty. This might result in significant accuracy degradation, whereas TripleBlind’s one-way encryption algorithms don’t add any noise to the dataset that would impair results. 

Differential privacy is suitable for situations with a higher degree of tolerance for error. For example, Apple keyboard suggestions – Apple doesn’t need to know exactly what you’re typing, but needs to know in general what people are typing to offer reasonable suggestions. 

Apple itself sets a strict limit on the number of contributions from a user in order to preserve their privacy. The reason is that the slightly biased noise used in differential privacy tends to average out over a large number of contributions, making it theoretically possible to determine information about a user’s activity over a large number of observations from a single user. It’s important to note that Apple doesn’t associate any identifiers with information collected using differential privacy.

The majority of the other approaches to data collaboration we’ve covered only work for tabular /columnar data; including homomorphic encryption, secure enclaves, tokenization. These approaches face severe challenges when it comes to producing high-performance, accurate models on complicated datasets like x-ray image analysis. However, TripleBlind is the solution to this problem since these images are encrypted – complying with HIPAA regulations.

 

TripleBlind uses data from outside sources to be used in our private infrastructure to compute and develop accurate diagnostics. Our Blind AI Pipeline ensures that the original data cannot be reversed engineered and is compliant with HIPAA regulations.

 

If you’re interested in knowing more about how you can safely and efficiently share data , please email contact@tripleblind.ai for a free demo. Don’t forget to follow TripleBlind on Twitter and LinkedIn for our latest updates. 

This is the final blog of our Competitor Blog Series where we compared TripleBlind’s technology to other approaches of data collaboration. If you missed the other blogs, you can check them out below!

 

Read other blogs in this series:

Business Agreements
Homomorphic Encryption
Synthetic Data
Blockchain
Tokenization, Masking and Hashing
Federated Learning