State Farm Mutual Automobile Insurance Company

Oscar Allan Arulfo

Michael Shawn Jacob

Leah Garcia

Manali Desai

Kalpana Aravabhumi

Joshua Robert Brown

This disclosure provides systems for generating customized datasets. An example dataset generator mines contacts from multiple members of an enterprise, applies a pattern recognition process to determine attributes of the contacts aligned with objectives of the enterprise, stores the contacts and associated attributes in a relational data structure, and through a machine learning process, generates a customized contact dataset of the contacts with attributes relevant to a user request, an event, or a notification received. The example dataset generator may also generate an action steps dataset for the user. The dataset generator may aggregate contacts from calls, chats, emails, SMS messages, and video feeds of an enterprise, apply a pattern recognition process to determine attributes of the contacts, and through a machine learning process, partition and distribute the contacts and associated action steps on respective dashboards of multiple customer service representatives of the enterprise.

Systems for generating customized datasets

Systems and methods are described for analyzing information relating to technical events associated with client devices in an organization (e.g., hardware and/or software malfunctions or performance inefficiencies originating at a client device or elsewhere in an organizational computing system). Particularly, machine learning techniques may use one or more trained artificial neural networks to classify technical events. Classifications of technical events may include, for example, causes of technical events, identifications of other affected devices, and/or steps for resolving technical events. Additionally, systems and methods are described for analyzing information relating to organizational ideas conceived of by client device users within the organization.

Systems and methods for analyzing a technical event

A task management platform generates an interactive display tasks based on multi-team activity data of different geographic locations across a plurality of distributed guided user interfaces (GUIs). Additionally the task management platform uses a distributed machine-learning based system to determine a suggested task item for a remote team based on multi-team activity data of different geographic locations.

Task management user interface (GUI)

Artificial intelligence systems and methods configured to predict team management decisions

Systems and methods may facilitate acquisition, distribution, and analysis of information relating to technical events associated with client electronic computing devices within an organization (e.g., malfunctions and other performance issues of hardware and/or software). Graphical user interfaces may facilitate the acquisition of system state information associated with client devices, as well as the acquisition of other user-provided contextual information relating to technical events. Additionally, the systems and methods may facilitate acquisition, distribution, and analysis of information relating to organizational ideas raised by client device users within the organization.

Growing community of inventors

Bloomington, IL, United States of America

Oscar Allan Arulfo