Vmware, Inc.

Boxer, Inc.

Airwatch LLC

Closedloop.ai Inc.

Andrew Everett Eye

Adam Cianfichi

Ian Ragsdale

Anthony Kueh

Neal Foster

Marshall Anne Busbee

Rob Worsnop

Dan Zeck

David Matthew DeCaprio

Joshua Taylor Gish

Thadeus Nathaniel Burgess

Carol Jeanne McCall

Systems herein supply hero cards that display contextual information and actions based on backend systems. The information and actions are related to a trigger content item in an application that does not have access to the backend systems. A hero agent running a user device can communicate the trigger content to a hero server. The hero server can determine which connectors to backend systems relate to the user device, and then can retrieve result information from one or more of the backend systems. The result information populates the hero card, which the hero agent displays within the application. Action buttons on the hero card cause the hero agent to contact one or more of the backend systems to cause an action to take place there.

Hero cards that display contextual information and actions for backend systems

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium to increase product usage. In some examples, a request to assign a task to a selected user is received. The selected user as a non-user of the task service. In response, task information and an identification of the task service is appended to an electronic document. Once the selected user has subscribed to the task service, the selected user is assigned to the task within the task service.

Email-based promotion for user adoption

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for explainable machine learning. In one aspect, a method comprises: obtaining a collection of data elements characterizing an entity; generating a plurality of features that collectively define a feature representation of the entity from the collection of data elements characterizing the entity; processing the feature representation of the entity using a machine learning model to generate a prediction for the entity; generating evidence data characterizing data elements from the collection of data elements that explain the prediction generated by the machine learning model for the entity; and providing an output comprising the prediction for the entity and the evidence data characterizing data elements from the collection of data elements that explain the prediction for the entity.

Explainable machine learning models

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for displaying, by the one or more processors, at least one graphical representation associated with an electronic document on a touchscreen display; and receiving, by the one or more processors, user input to the at least one graphical representation, the user input indicating a touchscreen gesture to the touchscreen display, and in response: determining a type of the touchscreen gesture; determining a degree of the touchscreen gesture; identifying one or more actions based on the type and the degree, each action of the one or more actions being executable to progress through a workflow; and displaying one or more action elements on the touchscreen display, each action element representing an action of the one or more actions.

Gesture-based workflow progression

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by the one or more processors, user input, the user input indicating an assignment of a particular task by a first user to a second user, the first user being a user of a product that provides the particular task; determining, by the one or more processors, that the second user is a non-user of the product and, in response: appending product promotion data to an electronic document, the product promotion data providing a summary of task-based action data that is associated with the second user; and transmitting the electronic document to the second user.

Growing community of inventors

Austin, TX, United States of America

Andrew Everett Eye