Ul LLC

Spencer Sharpe

Annie Ibrahim Rana

Saurav Acharya

Valeriy Liberman

Rashid Mehdiyev

Kyle Michael Caulfield

Lisa Epstein

Michael Arnold

James Cogley

Tricia Sheehan

Christian Dorn Anschuetz

Alan Cooney

Surekha Durvasula

Systems and methods for dynamically generating object models corresponding to regulations. According to certain aspects, a server computer may access a regulation and automatically generate a summary of the regulation based on a specific set of sentences. The server computer may additionally determine a set of topics and named-entity attributes for text within a regulation object model, as well as a probability that a topic or attribute is applicable to the regulation. Further, the server computer may generate and enrich object models according to the various analyses and avail the enriched object models for review by entities and users of regulatory compliance services.

Technologies for dynamically creating representations for regulations

Systems and methods for dynamically determining potentially applicability of product regulations to product protocols. According to certain aspects, an electronic device may access new or updated product regulations for various jurisdictions as well as product protocols associated with certain products. The electronic device may employ various data analyses technologies to determine which product regulations are potentially applicable to which product protocols. The electronic device may present information associated with the data analyses, and enable users to review information, further assess applicability, and make selections.

Technologies for dynamically assessing applicability of product regulations to product protocols

Systems and methods for classifying product feedback by an electronic device are described. According to certain aspects, an electronic device may receive consumer feedback entries associated with various products, where each entry may include an initial classification. The electronic device may analyze each entry using a machine learning model to determine a subsequent classification for the entry. When there is a mismatch between classifications, the electronic device may present information associated with the entry for review by a user, where the user may specify a final classification for the entry, and the electronic device may update the machine learning model for use in subsequent analyses.

Technologies for classifying feedback using machine learning models

Systems and methods for dynamically determining potentially applicability of product regulation updates to product profiles. According to certain aspects, an electronic device may access new or updated product regulation updates for various jurisdictions as well as product profiles associated with certain products. The electronic device may employ various data analysis technologies to determine which product regulation updates are potentially applicable to which product profiles. The electronic device may present information associated with the data analyses, and enable users to review information, further assess applicability, make selections, and interface and integrate with external systems to exchange information and insights.

Methods for dynamically assessing applicability of product regulation updates to product profiles

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Laramie, WY, United States of America

Spencer Sharpe