Unprecedented value from sensitive data

Mathematically proven privacy for the enterprise

Differential Privacy—data privacy done right

LeapYear is the world’s first platform for differentially private reporting, analytics and machine learning.  We enable enterprises across highly regulated industries to safely create value from their most sensitive datasets.

The platform embeds mathematically proven privacy into every computation, statistic and model enabling analysts and data scientists to generate insights from data without exposing the data itself.  Our customers safely leverage and share data across institutional silos, geographic borders and with third parties, all while preserving privacy and confidentiality.

LeapYear is deployed in production, at multi-petabyte scale, across global 1000 financial institutions, healthcare companies, and insurers.

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CURRENT METHODS

THE LEAPYEAR METHOD

Differential Privacy—data privacy done right

LeapYear is the world’s first platform for differentially private reporting, analytics and machine learning.  We enable enterprises across highly regulated industries to safely create value from their most sensitive datasets.

The platform embeds mathematically proven privacy into every computation, statistic and model enabling analysts and data scientists to generate insights from data without exposing the data itself.  Our customers safely leverage and share data across institutional silos, geographic borders and with third parties, all while preserving privacy and confidentiality.

LeapYear is deployed in production, at multi-petabyte scale, across global 1000 financial institutions, healthcare companies, and insurers.

  • 100M+

    Individual Records

  • 1 in 4

    US Population's Healthcare Data

  • 25 PB

    of Sensitive Data

  • $100B+

    Financial Transactions

PROTECTED WITH THE HIGHEST STANDARD OF DATA PRIVACY

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Next Up:

Aaron Roth, Professor of Computer and Information Science at the University of Pennsylvania, writes about why the time is now for differential privacy

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