Abstract: A text representation is received from a virtual assistant application on a user device. The text representation may be generated via a speech-to-text engine of the virtual assistant application from audio speech spoken by a customer. Device diagnostic data of the user device is also received from the virtual assistant application. An identifier of the customer is placed in an assistance queue. At least information in the text representation and the device diagnostic data is analyzed to determine an issue associated with the user device and a solution for resolving the issue, so that the solution is applied. In response to the identifier of the customer reaching a front of the assistance queue, session state information that includes at least the text representation and a description of the issue is provided to a support application. A voice support session is initiated between the support application and the virtual assistant application.

Abstract: A text representation is received from a virtual assistant application on a user device. The text representation may be generated via a speech-to-text engine of the virtual assistant application from audio speech spoken by a customer. Device diagnostic data of the user device is also received from the virtual assistant application. An identifier of the customer is placed in an assistance queue. At least information in the text representation and the device diagnostic data is analyzed to determine an issue associated with the user device and a solution for resolving the issue, so that the solution is applied. In response to the identifier of the customer reaching a front of the assistance queue, session state information that includes at least the text representation and a description of the issue is provided to a support application. A voice support session is initiated between the support application and the virtual assistant application.

Abstract: Systems and methods are described herein for providing multiple, different types of information for mobile devices and associated users to requesting systems, such as customer service systems provided by telecommunications carriers. The systems and methods may generate a single API that, when called by a requesting system (e.g., via a request transmitted by the requesting system that includes subscriber or device information), provides data collected from multiple, disparate data sources back to the requesting system via the single API.

Abstract: The present disclosure describes techniques for monitoring telemetry data that relates to processing of client data on one or more data cluster(s) and dynamically re-routing client data to another data cluster for processing, based on an analysis of the telemetry data. Particularly, a Load Balancing and Data Prioritization (LB-DP) system is described that can monitor telemetry data associated with processing client data, and further generate a cluster-telemetry metric for each data cluster that quantifies whether a user experience on a client device is likely to be influenced by a data latency (I.e. delay) in processing client data. In some examples, the LB-DP System may prioritize processing some instances of client data over others, based on client profile data that prioritizes some clients over others. In other examples, the LB-DP system may selectively schedule a later time interval for processing of an instance of client data.

Abstract: The present disclosure describes techniques for monitoring telemetry data that relates to processing of client data on one or more data cluster(s) and dynamically re-routing client data to another data cluster for processing, based on an analysis of the telemetry data. Particularly, a Load Balancing and Data Prioritization (LB-DP) system is described that can monitor telemetry data associated with processing client data, and further generate a cluster-telemetry metric for each data cluster that quantifies whether a user experience on a client device is likely to be influenced by a data latency (I.e. delay) in processing client data. In some examples, the LB-DP System may prioritize processing some instances of client data over others, based on client profile data that prioritizes some clients over others. In other examples, the LB-DP system may selectively schedule a later time interval for processing of an instance of client data.

Abstract: Systems and methods are described herein for providing multiple, different types of information for mobile devices and associated users to requesting systems, such as customer service systems provided by telecommunications carriers. The systems and methods may generate a single API that, when called by a requesting system (e.g., via a request transmitted by the requesting system that includes subscriber or device information), provides data collected from multiple, disparate data sources back to the requesting system via the single API.

Abstract: Systems and methods are described herein for providing multiple, different types of information for mobile devices and associated users to requesting systems, such as customer service systems provided by telecommunications carriers. The systems and methods may generate a single API that, when called by a requesting system (e.g., via a request transmitted by the requesting system that includes subscriber or device information), provides data collected from multiple, disparate data sources back to the requesting system via the single API.

Abstract: The present disclosure describes techniques for monitoring telemetry data that relates to processing of client data on one or more data cluster(s) and dynamically re-routing client data to another data cluster for processing, based on an analysis of the telemetry data. Particularly, a Load Balancing and Data Prioritization (LB-DP) system is described that can monitor telemetry data associated with processing client data, and further generate a cluster-telemetry metric for each data cluster that quantifies whether a user experience on a client device is likely to be influenced by a data latency (I.e. delay) in processing client data. In some examples, the LB-DP System may prioritize processing some instances of client data over others, based on client profile data that prioritizes some clients over others. In other examples, the LB-DP system may selectively schedule a later time interval for processing of an instance of client data.

Abstract: The present disclosure describes techniques for monitoring telemetry data that relates to processing of client data on one or more data cluster(s) and dynamically re-routing client data to another data cluster for processing, based on an analysis of the telemetry data. Particularly, a Load Balancing and Data Prioritization (LB-DP) system is described that can monitor telemetry data associated with processing client data, and further generate a cluster-telemetry metric for each data cluster that quantifies whether a user experience on a client device is likely to be influenced by a data latency (I.e. delay) in processing client data. In some examples, the LB-DP System may prioritize processing some instances of client data over others, based on client profile data that prioritizes some clients over others. In other examples, the LB-DP system may selectively schedule a later time interval for processing of an instance of client data.

Abstract: Systems and methods are described herein for providing multiple, different types of information for mobile devices and associated users to requesting systems, such as customer service systems provided by telecommunications carriers. The systems and methods may generate a single API that, when called by a requesting system (e.g., via a request transmitted by the requesting system that includes subscriber or device information), provides data collected from multiple, disparate data sources back to the requesting system via the single API.

Abstract: Systems and methods are described herein for providing multiple, different types of information for mobile devices and associated users to requesting systems, such as customer service systems provided by telecommunications carriers. The systems and methods may generate a single API that, when called by a requesting system (e.g., via a request transmitted by the requesting system that includes subscriber or device information), provides data collected from multiple, disparate data sources back to the requesting system via the single API.

Abstract: Systems and methods are described herein for providing multiple, different types of information for mobile devices and associated users to requesting systems, such as customer service systems provided by telecommunications carriers. The systems and methods may generate a single API that, when called by a requesting system (e.g., via a request transmitted by the requesting system that includes subscriber or device information), provides data collected from multiple, disparate data sources back to the requesting system via the single API.

Abstract: In some implementations, a computing device may download a campaign from a server. The campaign may include a trigger and one or more actions associated with the trigger. In response to detecting that the trigger occurred, the computing device may perform the one or more actions associated with the trigger. The trigger may comprise an event that occurs at the computing device or a short message service (SMS) message that originates from the server.

Abstract: In some implementations, a computing device may download a campaign from a server. The campaign may include a trigger and one or more actions associated with the trigger. In response to detecting that the trigger occurred, the computing device may perform the one or more actions associated with the trigger. The trigger may comprise an event that occurs at the computing device or a short message service (SMS) message that originates from the server.

Abstract: A system which includes at least one ultrasound data collection device which is programmable to carry out a specific ultrasound procedure on a selected part of a human body of a patient. The resulting ultrasound data is transmitted via a local server at the site of the data collection device to the internet and from there to a web database server which processes the raw ultrasound data to produce medical result information, including ultrasound images, which is then sent to a skilled technician, who accepts the results, rejects or edits them. Accepted medical results are transmitted back to the medical practitioner, while edited medical results are reprocessed, the results of which are transmitted to the medical practitioner.

Abstract: A system which includes at least one ultrasound data collection device which is programmable to carry out a specific ultrasound procedure on a selected part of a human body of a patient. The resulting ultrasound data is transmitted via a local server at the site of the data collection device to the internet and from there to a web database server which processes the raw ultrasound data to produce medical result information, including ultrasound images, which is then sent to a skilled technician, who accepts the results, rejects or edits them. Accepted medical results are transmitted back to the medical practitioner, while edited medical results are reprocessed, the results of which are transmitted to the medical practitioner.