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Safely use, share
& sell insights from
personal data
Tumult Labs’ platform operationalizes privacy-safe datasharing for the enterprise
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trusted by
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Solutions by industry
Public Sector
Increase the rate and usefulness of publications and ensure delivery of your mandated calendar.
Advertising
Enable data-driven product and campaign decision-making and reporting while protecting individual privacy.
Banking and Finance
Share valuable macro and micro insights while ensuring privacy protection and compliance.
How we use Differential Privacy
Extract value from personal data, while maintaining privacy
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Raw personal data: too sensitive to use
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Protective transformation, with Differential Privacy
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Safe to share summary data. DP offers valuable insights with guaranteed privacy.
Differential Privacy (DP) powers a responsible, defensible, future-proof approach to privacy.
Use Cases
We support your deployment of differential privacy for a powerful set of use cases.
Systematize disclosure avoidance
Safeguard sensitive information; reduce the risk of privacy breach.
Assure safe internal data
sharing and data reuse
Enhance data-driven decision-making and innovation.
Enable secure external data
sharing and publishing
Enable responsible data sharing and data monetization.
Unlock new data collaboration opportunities with clean rooms
Facilitate secure multi-party collaboration, including joint research and analysis.
Enable data monetization
Access new revenue opportunities while maintaining regulatory compliance.
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Case Study
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Illuminating college outcomes, while protecting privacy
Public Sector
Joining sensitive data sets from the Department of Education and the IRS in a way that protected privacy resulted in College Scorecard - a platform that allows students and families to simultaneously consider the cost and evidenced outcomes of a range of possible degrees.
Learn more
About us
Why choose Tumult?
Founded by pre-eminent experts in Differential Privacy, and informed by collaborations with vanguard enterprises, Tumult is building the first platform that operationalizes DP.
Tumult brings together a world-class team, passionate about expanding the use and sharing of data while respecting individual privacy.
Recent articles
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Perspective
Joseph P. Near & David Darais
“Guidelines for Evaluating Differential Privacy Guarantees” NIST Special Publication
“Data analytics is becoming an essential tool to help organizations make sense of the enormous volume of data being generated by information technologies. (...) However, when the data being analyzed relates to or affects individuals, privacy risks can arise. These privacy risks can limit or prevent entities from realizing the full potential of data.”
Perspective
Dr. Rachel Cummings
Associate Professor
Columbia University
“If you focus on privacy and make it a priority, in the end it leads to better data that can be monetized.”
"Are You Afraid of Data? Balancing Privacy and Data Monetization," CPO Magazine
Perspective
Damien Desfontaines
Staff Scientist
Tumult Labs
“Differential privacy is the only approach that offers a rigorous guarantee that individuals cannot be singled out based on the results of queries executed in the cleanroom.”
Perspective
U.S. Census
“Modern computers and today’s data-rich world have rendered the Census Bureau’s traditional confidentiality protection methods obsolete. Those legacy methods are no match for hackers aiming to piece together the identities of the people and businesses behind published data. ”
-- "2020 Decennial Census: Processing the Count: Disclosure Avoidance Modernization"
Perspective
Allison Schiff
Managing Editor
Ad Exchanger
“While differential privacy began as an academic notion…ad tech companies need to know about it, too, and some even see it as the future of privacy protection.”
Perspective
John Seely Brown
Former Chief Scientist
Xerox Corp
“In the world of data, sharing is not about giving away, it's about co-creating value.”
Testimonial
Hal Triedman
Senior Privacy Engineer
Wikimedia Foundation
"With Tumult Labs' open source software and expertise in technical implementation, the Wikimedia Foundation team is now able to release more granular, equitable, and safe data about how readers are using our platforms."
Perspective
Miguel Cardona, PhD.
Secretary
U.S. Department of Education
"We need a system that’s inclusive, that delivers value, and that produces equitable outcomes. We need transparency in data more now than ever before."
Testimonial
John M. Abowd, PhD.
Chief Scientist
U.S. Census Bureau
"We turned to Tumult Labs to design and implement our most challenging data release problem. Tumult’s excellent tools ensured fitness for use while provably guaranteeing the confidentiality of the underlying microdata. Tumult’s software will be reused within the Census Bureau for the next decade."
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