Assigning support tickets to support agents is described. A system receives support tickets and trains a machine-learning model to identify support agents who had experiences resolving support tickets of multiple complexities. The system receives a support ticket, identifies a topic of the support ticket, and estimates a complexity of the support ticket. The system identifies support agents who have skills handling the topic of the support ticket. The machine-learning model identifies support agents who have experiences resolving support tickets of the estimated complexity. The system projects workload availabilities, of identified support agents, for the support ticket. The system generates support agent scores based on the skills handling the topic, the experiences resolving support tickets of the estimated complexity, and the projected workload availabilities for the support ticket. The system assigns, based on the support agent scores, the support ticket to an identified support agent.

An example method includes providing third party access to listen to a call and the ability to inject audio into an isolated audio portion of the call by using a switch controller within a mobile virtual network operator (MVNO) platform. The switch controller can to separate a call into multiple audio portions. The example method can further include collecting and warehousing call metadata and providing access to isolated audio portions via an external database, web object, API, etc.

Responding to a data subject access request includes receiving the request and identifying the requestor and source. In response to identifying the requestor and source, a computer processor determines whether the data subject access request is subject to fulfillment constraints, including whether the requestor or source is malicious. If so, then the computer processor denies the request or requests a processing fee prior to fulfillment. If not, then the computer processor fulfills the request.

An improved system and method for providing data analytics management (DAM), in particular for wireless networks having multiple domains, is disclosed. Some embodiments utilize a hierarchical DAM structure. Such a hierarchy includes a Global DAM function which provides inter network DAM, and domain DAM functions which provide intra network DAM. Some embodiments utilize a plurality of local DAM functions within a domain. In some embodiments, the global DAM can be implemented by a third party. In other embodiments, different networks inter operate by utilizing virtual network slices over non-owned infrastructure to provide what appears to be a global network by each operator. For such embodiments, DAM can be performed on a per slice basis.

A device receives, based on a user interaction with a chatbot, request data for a request for a service associated with a software tool that is part of a service management system. The device identifies, based on the request data, the service that is being requested and a first set of entity data for a first set of entities relating to the service. The device obtains a second set of entity data for a second set of entities by using an application programming interface (API) to reference a data structure that is associated with the service management system and that stores the second set of entity data. The device causes one or more components of the service management system to use the first set of entity data to execute a set of actions to perform the service.

A method is provided for providing mobile device support services. The method may include monitoring a mobile device status. The method may additionally include performing device diagnostics based at least in part on captured device status data to identify potential faults that may affect mobile device functionality. A corresponding system, apparatus, and computer program product are also provided.

First resource utilization information for a first customer of a cloud platform and second resource utilization information for a second customer of the cloud platform are accessed. A first prediction regarding future resource utilization by the first customer and a second prediction regarding future resource utilization by the second customer are determined. A resource reallocation recommendation that recommends reallocating one or more resources between the first customer and the second customer is determined, based on the first prediction and the second prediction. The resource reallocation recommendation is provided.

A resource allocation service can provide for the limited redelivery of events for processing using a set of virtual resources. A customer can provide code for execution, and the service can allocate resource instances configured to execute the code in response to various events. The processing for an event may not be completed by a single resource instance. When a resource instance is to end processing, the instance can capture state information to be returned as checkpoint data for the event. When the processing result is received, the service determines whether checkpoint data was included, which functions as a request for further processing. The service can then place the event data back in an event queue for redelivery and additional processing. A customer can specify a time limit or a retry limit such that an event can only undergo up to a maximum amount of processing before the event is failed.

A method for data processing may include receiving a communication from a parent span, the communication including a data portion and a header portion. The header portion may include an identifier of an originating service that produced the communication, an identifier of a transaction for the communication, and an identifier of the parent span. The method may include identifying the parent span and the originating serviced based on the header portion. The method may also include performing a system trace process of the communication throughout the transaction based on the parent span and the originating service.

A business process and supporting system that incorporates the resulting cloud-based workflow to procure and manage broadband and related services. The business process is divided into its component steps. All communication is abstracted into structured data allowing for a systematic and error free process. Tools are built into the system to enhance ease of use, and eliminating time wasting effort. An algorithmic approach to matching Customer needs to ISP offerings provides a very efficient and cost-effective way to manage a very real need for multi-location businesses.