Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.