Brent Scheibelhut

This inventor holds 33 USPTO granted patents and 59 published patent applications, primarily in Machine Learning Applications. Top assignee: Maplebear Inc.. Active years: 2025-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Brent Scheibelhut. Retrieved from https://idiyas.com/inventor/brent-scheibelhut

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank

USPTO Granted Patents = 33 (Patent Applications = 59)

% Patents Active = 24.2

Average Co-Inventor Count = 4.1

ph-index = 1

Company Filing History:

31 out of 355

Maplebear Inc.

patents

where one patent can have more than one assignee

Years Active: 2025-2026

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Areas of Expertise:

Personalized Communication

Smart Cart Systems

Demand Prediction

Error Detection

Item Findability

Quality Assessment

Recipe Suggestions

Natural Language Processing

Augmented Reality

User Inquiries

Image Recognition

Data Clustering

33 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12770178 - Machine learned model for selecting actions for fulfilling order with out-of-stock items (2026-10-20),

2. 12762605 - Automatic routing of user inquiries using machine-learning models (2026-10-13),

3. 12755313 - Using a trained machine-learning model to facilitate picking items in a warehouse (2026-10-06),

4. 12749091 - Artificial intelligence agent for personalized communication with users of an online system (2026-09-29),

5. 12749047 - Automated identification of items placed in a cart and routing based on same (2026-09-29),

6. 12743717 - Using trained machine-learning model of an online system to predict timing of state change of variable state item (2026-09-22),

7. 12743672 - Smart expiration determination of grocery items (2026-09-22),

8. 12705574 - Machine learned model for proactively selecting a remedial action using before receiving a notification of a problem with an order (2026-08-11),

9. 12688527 - User interface for selecting sources for an online concierge system with a quick-add option for an item-source pair (2026-07-21),

10. 12675816 - Using a machine learning model to predict a user's quantity ceiling for different categories of items in a catalog (2026-07-07),

11. 12675813 - Generating recommendations for adjustment actions using a trained model of an online system (2026-07-07),

12. 12675381 - Device error priority assignment generation for smart cart systems (2026-07-07),

13. 12670471 - Machine learning model for predicting future availability of items to evaluate potential replacement items during order fulfillment (2026-06-30),

14. 12664579 - Selectively displaying videos by an online system (2026-06-23),

15. 12664524 - Smart cart issue prediction with remedial workflow (2026-06-23),

Title: Brent Scheibelhut: Innovator in Predictive Modeling and Online Concierge Systems

Introduction

Brent Scheibelhut is a notable inventor based in Toronto, Canada. He has made significant contributions to the fields of predictive modeling and online shopping through his innovative patents. With a total of 33 patents, Brent's work focuses on enhancing user experience in retail environments.

Latest Patents

One of Brent's latest patents involves using a trained model to predict a user's price sensitivity based on data acquired from in-store sensors. This online system generates input data by gathering replacement data via a user interface at a device associated with the user and/or in-store behavior data related to the replacement of items performed by the user at a retailer's location. The system applies a price sensitivity model to predict a price sensitivity score for the user, which helps in identifying actions to prompt the user to convert items.

Another significant patent is for sharing and generating prepopulated carts by an online concierge system. This system facilitates ordering, procurement, and delivery of items to customers from physical retailers based on shared cart recommendations. It utilizes customer identifying information and other data sources to recommend prepopulated shared carts that may interest customers. These carts can be created and shared by other users or stakeholders in the selling of items through the online concierge system.

Career Highlights

Brent currently works at Maplebear Inc., where he continues to develop innovative solutions that enhance the online shopping experience. His work is characterized by a strong focus on integrating machine learning techniques to improve user engagement and satisfaction.

Collaborations

Brent collaborates with talented individuals such as Shaun Navin Maharaj and Mark Oberemk, contributing to a dynamic work environment that fosters creativity and innovation.

Conclusion

Brent Scheibelhut is a forward-thinking inventor whose work in predictive modeling and online concierge systems is shaping the future of retail. His innovative patents reflect a commitment to improving user experiences in the shopping landscape.

Profile summary based on public USPTO records.

Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]

59 patents pending: