For the Inventor, By the Inventor

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San Francisco, CA, United States of America

Sift Science, Inc.

USPTO Granted Patents = 43

Forward Citations = 319

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56 inventors (with patents filed for the assignee):

Fred Sadaghiani (19 out of 19 patents)

Wei Liu (17 out of 18 patents)

Jacob Burnim (12 out of 12 patents)

4. Alex Paino (12 out of 12 patents)

5. Keren Gu (11 out of 11 patents)

6. Noah Grant (8 out of 8 patents)

7. Eugenia Ho (7 out of 7 patents)

8. Hui Wang (6 out of 6 patents)

9. Pradhan Bagur Umesh (5 out of 5 patents)

10. Rishabh Kothari (4 out of 5 patents)

11. Kostyantyn Gurnov (4 out of 5 patents)

12. Vera Dadok (4 out of 4 patents)

13. Yuan Zhuang (4 out of 4 patents)

14. Irving Chen (4 out of 4 patents)

15. Gary Lee (4 out of 5 patents)

Core Competencies:

Digital Threat Mitigation

Machine Learning

Fraud Detection

Automated Decisioning

Anomaly Detection

Content Threat Detection

Automated Labeling

Probationary Workflows

Multi-Factor Authentication

Data Sampling

Threat Scoring

User Threat Detection

43 patents: Sort by Forward Citations

1. 12375500 - Systems and methods for digital threat assessment and mitigation using t-digest score distribution representations and percentile-based threat scoring in a digital threat mitigation platform (2025-07-29),

2. 12273356 - Systems and methods for digital threat assessment and mitigation using t-digest score distribution representations and percentile-based threat scoring in a digital threat mitigation platform (2025-04-08),

3. 12143402 - Systems and methods for accelerating a disposition of digital dispute events in a machine learning-based digital threat mitigation platform (2024-11-12),

4. 12047401 - Systems and methods for machine learning-based detection of an automated fraud attack or an automated abuse attack (2024-07-23),

5. 11916927 - Systems and methods for accelerating a disposition of digital dispute events in a machine learning-based digital threat mitigation platform (2024-02-27),

6. 11887126 - Systems and methods for generating a probationary automated-decisioning workflow in a machine learning-task oriented digital threat or digital abuse mitigation system (2024-01-30),

7. 11841941 - Systems and methods for accelerated detection and replacement of anomalous machine learning-based ensembles and intelligent generation of anomalous artifacts for anomalous ensembles (2023-12-12),

8. 11777962 - Systems and methods for machine learning-based detection of an automated fraud attack or an automated abuse attack (2023-10-03),

9. 11720668 - Systems and methods for accelerated detection and replacement of anomalous machine learning-based digital threat scoring ensembles and intelligent generation of anomalous artifacts for anomalous ensembles (2023-08-08),

10. 11645386 - Systems and methods for automated labeling of subscriber digital event data in a machine learning-based digital threat mitigation platform (2023-05-09),

11. 11620653 - Systems and methods for configuring and implementing a malicious account testing machine learning model in a machine learning-based digital threat mitigation platform (2023-04-04),

12. 11573882 - Systems and methods for optimizing a machine learning-informed automated decisioning workflow in a machine learning task-oriented digital threat mitigation platform (2023-02-07),

13. 11528290 - Systems and methods for machine learning-based digital content clustering, digital content threat detection, and digital content threat remediation in machine learning-based digital threat mitigation platform (2022-12-13),

14. 11496501 - Systems and methods for an adaptive sampling of unlabeled data samples for constructing an informative training data corpus that improves a training and predictive accuracy of a machine learning model (2022-11-08),

15. 11481490 - Systems and methods for automated labeling of subscriber digital event data in a machine learning-based digital threat mitigation platform (2022-10-25),

Sift Science, Inc. provides an online fraud detection and prevention platform that helps companies of all sizes prevent fraudulent activities. Their cutting-edge technology combines machine learning, device identification, and global network intelligence to analyze and identify patterns of fraudulent behavior in real-time. With their customizable solutions, businesses can protect themselves from account takeover, payment fraud, fake accounts, and other fraudulent activities, enabling a safe and secure online environment for their customers.

This text is generated by artificial intelligence and may not be accurate.

Company Badge

USPTO Data Jan 1 1976 - Sep 29 2026

Sift Science, Inc.

43 Patents

#106 in San Francisco, CA

#1,898 in California

#8,084 in US

#16,010 in the World

San Francisco, CA, United States of America

Sift Science, Inc.

Forward Citations = 319

56 inventors:

Fred Sadaghiani (19 out of 19 patents)

Wei Liu (17 out of 18 patents)

Jacob Burnim (12 out of 12 patents)

4. Alex Paino (12 out of 12 patents)

5. Keren Gu (11 out of 11 patents)

Please report any incorrect information to [email protected]

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