USPTO Patent US12587493B2: Generative ML for Personalized Knowledge Content

ChangeBridge: Patent Grants - AI & Computing (G06N)

Published March 24th, 2026

Detected March 25th, 2026

Summary

The USPTO has granted patent US12587493B2 to Cisco Technology, Inc. for a generative machine learning model designed to create personalized knowledge session content. The patent covers methods for user grouping, personalized message generation, and updating models based on feedback.

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What changed

This document details the granting of US Patent US12587493B2 to Cisco Technology, Inc. The patent describes a system and method for generating personalized knowledge session content using generative machine learning. Key aspects include processing user profile and service description data to assign users to groups, creating personalized messages via machine learning models, and updating these models and data based on collected feedback.

As this is a patent grant, it does not impose new regulatory obligations on entities. However, it signifies intellectual property protection for Cisco Technology, Inc. in the area of AI-driven content personalization. Companies operating in similar spaces, particularly those developing or utilizing generative AI for user engagement, should be aware of this granted patent and its claims.

Source document (simplified)

← USPTO Patent Grants

Generative machine learning model for personalized knowledge session content

Grant US12587493B2 Kind: B2 Mar 24, 2026

Assignee

CISCO TECHNOLOGY, INC.

Inventors

Qixu Gong, Benjamin L. Chang, Qihong Shao, David C. White, Jr.

Abstract

A method, computer system, and computer program product are provided for generating personalized knowledge session content using a generative machine learning model. User profile data of a plurality of users and service description data that is descriptive of a service are processed to assign the plurality of users to a plurality of user groups. A personalized message is generated for each user group based on the user profile data and the service description data, wherein the personalized message is generated using one or more machine learning models. Each personalized message is provided to each user group and feedback data is collected based on the providing of each personalized message. Based on analyzing of the feedback data, one or more of: the user profile data, the one or more machine learning models, and the service description data are updated.