Sift Science

Sift Science combat fraud with extensive scale machine learning. Machine learning lets a computer system perceive examples of fraudulent behavior focused around past samples. What makes expansive scale machine learning special is the determination of examples educated. Our framework has adapted in excess of one million fraud examples and numbering, including particular page navigation sequences, IP reaches, email location examples, graph connectivity structures, and writing styles that foresee fraudulent activity.

Sift Science has built the world’s most advanced fraud detection system. Using large-scale machine learning technology to predict fraudulent behavior with unparalleled accuracy, Sift Science leverages a global network of fraud data. Catch the fraud that is unique to your business and train your customized model to stop fraudsters in real time. Our flexible, adaptive, and automated solution helps businesses of all sizes detect and prevent fraud, before it hits your bottom line.



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Countries Supported

North America


Other, Technology


Subscription, Free Trial

Size of Customers

Global Enterprise

Year Founded

June, 2011


Funding Received from Investors

$23.6 Million


Alex Rampell, Alexis Ohanian, Chris Dixon, First Round, Founder Collective, Garry Tan, Harjeet Taggar, Kevin Scott, Lee Linden, Marc Benioff, Max Levchin, Rich Barton, Spark Capital, SV Angel, Union Square Ventures, Y Combinator

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