Abstract: Systems and methods for generating notifications based on extracted data from documents using a machine learning algorithm. The method includes receiving a document uploaded by a user including data corresponding to the user. The method further includes receiving an indication from the user granting permission to extract the data from the document. The method also includes extracting the data from the document using optical character recognition. The method further includes determining a document type based on the extracted data and document format data using a machine learning algorithm. The method also includes verifying the extracted data based on the determined document type and user data. The method also includes identifying a triggering event corresponding to the document based on the extracted data and the user data. The method further includes generating a notification corresponding to the triggering event.

Abstract: Systems and methods are described for automating retrieval of application data prior to wireless network outages and rendering mobile device UIs during the outages. The system includes a server and database of data object files corresponding to features of applications executable on the mobile device. The mobile device receives a notification from the server before a predicted network outage, and sends back a request including parameters indicating resource status. The mobile device receives a response including a data object file from the database and automatically invokes a network bot, UI bot, and navigation bot. The network bot retrieves application data from a web server based on an object from the data object file. The navigation bot generates a navigation handle based on an object from the data object file, and the UI bot renders a UI based upon a UI object from the data object file and the navigation handle.

Abstract: Systems and methods for generating notifications based on extracted data from documents using a machine learning algorithm. The method includes receiving a document uploaded by a user including data corresponding to the user. The method further includes receiving an indication from the user granting permission to extract the data from the document. The method also includes extracting the data from the document using optical character recognition. The method further includes determining a document type based on the extracted data and document format data using a machine learning algorithm. The method also includes verifying the extracted data based on the determined document type and user data. The method also includes identifying a triggering event corresponding to the document based on the extracted data and the user data. The method further includes generating a notification corresponding to the triggering event.

Abstract: Systems and methods are described for automating retrieval of application data prior to wireless network outages and rendering mobile device UIs during the outages. The system includes a server and database of data object files corresponding to features of applications executable on the mobile device. The mobile device receives a notification from the server before a predicted network outage, and sends back a request including parameters indicating resource status. The mobile device receives a response including a data object file from the database and automatically invokes a network bot, UI bot, and navigation bot. The network bot retrieves application data from a web server based on an object from the data object file. The navigation bot generates a navigation handle based on an object from the data object file, and the UI bot renders a UI based upon a UI object from the data object file and the navigation handle.

Abstract: Methods and apparatuses are described for generating and displaying custom-selected content for a mobile application. A mobile device captures a request to launch an application and determines content cards eligible to be displayed. A user-specific content classification model is generated for selecting one of the content cards to be displayed, where the mobile device identifies historical usage characteristics and transmits the historical usage characteristics to a server, which generates the user-specific content classification model based upon the historical usage characteristics and transmits the user-specific content classification model to the mobile device. The mobile device executes the user-specific content classification model to select one or more content cards to be displayed and launches the application to display the selected content cards.

Abstract: A computer-implemented method is provided for automatically masking data for display in a mobile computing device. The computer-implemented method includes receiving a request to display data on the mobile computing device and detecting a physical location of the mobile computing device, a time corresponding to the request, and at least one network characteristic of a wireless network on which the mobile computing device is making the request. The method also includes automatically determining whether to mask the data for display in the mobile computing device based on the physical location, the time, and the at least one network characteristic. The method further includes responsive to determining to mask the data, applying one or more masking rules to the data.

Abstract: A computer-implemented method is provided for automatically masking data for display in a mobile computing device. The computer-implemented method includes receiving a request to display data on the mobile computing device and detecting a physical location of the mobile computing device, a time corresponding to the request, and at least one network characteristic of a wireless network on which the mobile computing device is making the request. The method also includes automatically determining whether to mask the data for display in the mobile computing device based on the physical location, the time, and the at least one network characteristic. The method further includes responsive to determining to mask the data, applying one or more masking rules to the data.