An example system for dynamic agent management involving multiple queues is presented. The system may include a remote network management platform that manages a network by way of a computational instance. A first group and a second group of agents may be assigned to address work items in a first queue in the computational instance. The second group may also be assigned to address and prioritize work items in a second queue in the computational instance. A computing device within the computational instance may assign a work item originating from a client device in the managed network into the first queue according to routing rules. The assignment may cause a timer to record a duration that the work item is in the first queue. The computing device may assign one of the second group of agents to address the work item based on the duration exceeding a pre-determined value.

Certain exemplary aspects of the present disclosure are directed to a data-communications system including a networked contact center for which, in an example embodiment, a communication is received by a networked contact center. In determining whether to allow the communication to reach contact center resources, a contact rate value is examined. The contact rate value may represent an allowable quantity of contact within a time interval. For some example embodiments, a determination of whether the network contact center is to accept or reject the communication is made based on the contact rate value.

A computerized-method for service monitoring and rate limiting for a service for a request router in a SaaS-platform-contact-center is provided herein. When a service-monitoring-module for a microservice of the SaaS-platform-contact-center is operating and a request-router is in a throttle-mode for a service-of-the-microservice, operating a Tenants Prioritization (TP) module. The TP module includes: determining a tenant-tier-level having a determined quota-of-service-requests; receiving a degradation-level from the service-monitoring-module, for a preconfigured-period; reducing corresponding predefined total-number-of-allowed-requests by a first-threshold, when the degradation-level of the service-of-the-microservice has degraded by a second-threshold, during the preconfigured-period; increasing the corresponding predefined total-number-of-allowed-requests by the first-threshold, when the degradation-level of the service-of-the-microservice has improved by the second-threshold, during the preconfigured period; and instructing the request-router to get out of throttle-mode for the service-of-the-microservice, when the degradation-level of the service-of-the-microservice has improved by the second-threshold during the preconfigured period and there is an indication that the service-of-the-microservice has been degraded.

A computerized-method for redirecting, inbound-voice-interactions to digital channels in a contact center, is provided herein. The computerized-method includes: (i) operating a digital-qualifier module to determine a digital-medium-transition-quotient, of an inbound-voice-interaction of a customer in an inbound-queue. The digital-medium-transition-quotient is an indication of a level of suitability of a digital-communication-channel to resolve a customer issue; (ii) operating an interaction-redirection module to determine a digital-communication-channel for redirection of the inbound-voice-interaction, based on customer-preference and the determined digital-medium-transition-quotient; and (iii) forwarding the inbound-voice-interaction and the determined digital-communication-channel to an Automatic Call Distribution (ACD) system to be carried-out by an agent via the determined digital-communication-channel when the determined digital-medium-transition-quotient is above a preconfigured threshold.

Systems and methods are provided for dynamic routing of an automated telephony system. The automated telephony system facilitates functions desired by a caller, via an automated call with the caller. A machine-learning analysis system extracts data from the automated call, performs machine-learning via the extracted data to identify a likely motivation of the caller associated with the automated call, and provides the likely motivation to the automated telephony system. The automated telephony system then receive the likely motivation from the machine-learning analysis system and dynamically routes the automated call based upon the likely motivation.

Techniques for behavioral pairing in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, at least one behavioral pairing constraint; and applying, by the at least one computer processor, the at least one behavioral pairing constraint to the task assignment system to controllably reduce performance of the task assignment system.

Technologies for monitoring interactions between customers and agents include an interaction management computing device communicatively coupling a customer computing device and an agent computing device to facilitate a support call interaction. The interaction management computing device is configured to receive a video call from a customer and perform a facial recognition analysis of the customer based on images of the customer received with the video call. Additionally, the interaction management computing device is configured to determine a probable emotional state of the customer as a function of the facial recognition analysis of the customer and insert the video call into a service queue as a function of the probable emotional state of the customer. Additional embodiments are described herein.

A computer-assisted patient navigational communication system for receiving electronic and oral communications from a patient, scanning data to determine the medical needs of the patient, and displaying relevant information to appropriate medical personnel who can immediately advise the patient of the most appropriate source of medical assistance relating to the patient’s identified symptoms.

This document discusses, among other things, limiting contact to a networked contact center that is a host to multiple tenants. In an example embodiment, a communication is received by a networked contact center. In determining whether to allow the communication to reach contact center resources, a contact rate value may be examined. The contact rate value may represent an allowable quantity of contact within a time interval. For some example embodiments, a determination of whether the network contact center is to accept or reject the communication is made based on the contact rate value.

A call center system has a computerized server executing software (SW) from a machine-readable medium, a data collection function of the SW enabled for collecting data regarding incoming transactions, a data processing function coupled to the data collection engine and enabled for processing the data collected against a set of business rules, the data processing function determining a priority level for individual ones of the incoming transactions, and a distribution function enabled for distributing a priority indication determined by the data processing function to one or more presentation interfaces accessible to agents, at or near the time the associated transaction is engaged by the agent.