Abstract: Systems and methods for capturing sentiments and delivering elevated proactive user experience are disclosed.

Abstract: A system and a method for facilitating a processing of a service request is provided. The method includes: accessing a plurality of previously received service requests; receiving a first new service request; determining a handling protocol for the first new service request; adding the received first new service request to the plurality of previously received service requests to generate an updated list of open service requests; and displaying a listing of a least a subset of the updated list of open service requests. The handling protocol includes a priority ranking of the first new service request and an identification of a proposed technician for resolving the corresponding problem. The determination of the handling protocol is performed by assigning weights to each of a set of predefined parameters and algorithmically combining the assigned weights to obtain an overall priority score.

Abstract: A system and a method for facilitating a processing of a service request is provided. The method includes: accessing a plurality of previously received service requests; receiving a first new service request; determining a handling protocol for the first new service request; adding the received first new service request to the plurality of previously received service requests to generate an updated list of open service requests; and displaying a listing of a least a subset of the updated list of open service requests. The handling protocol includes a priority ranking of the first new service request and an identification of a proposed technician for resolving the corresponding problem. The determination of the handling protocol is performed by assigning weights to each of a set of predefined parameters and algorithmically combining the assigned weights to obtain an overall priority score.

Abstract: Apparatus and methods related to de-identifying data are provided. An example method includes receiving, by a computing device, input data comprising text. The method further includes applying a neural network to a tokenized representation of the input text, to generate an embedding based on contextual information associated with an entity. The method also includes predicting, by the neural network and based on the embedding, whether the input data comprises protected data in the text, wherein the neural network has been trained on a training dataset that has been partially customized based on the entity. The method further includes de-identifying the protected data in the text upon a determination that the input data comprises protected data in the text.