Abstract: As described herein, an automated call distribution system, method, and computer program are provided that use multi-skill based routing. An opportunity to make customer service-related contact with a customer is detected. A plurality of skills required to handle the customer service-related contact is determined, where each required skill is defined as a skill type and one or more corresponding skill values. A plurality of skills of each customer service agent among one or more available customer service agents is determined. The customer service-related contact is managed based on the plurality of skills required to handle the customer service-related contact and the plurality of skills of each customer service agent among the one or more available customer service agents.

Abstract: A redirection and messaging system receives telephony information identifying a caller and call context from a telephony system. The system selects one of a plurality of messaging operators based on the call context, optionally sends an introductory message to the caller via a messaging service, and generates a message interface for the selected message operator. The message interface includes the caller and call context and any messages sent between the caller and the selected message operator, with an input interface allowing the selected message operator to input and send messages to the caller.

Abstract: A method of providing blockchain wireless services in a controlled environment is provided. The method comprises a wireless communication device associated with an inmate of a controlled environment receiving one of a voice and video call from a device external to the controlled environment. The method further comprises the device placing the received call into a hold state and sending a request for validation of the call via a blockchain, the request identifying at least parties to the call. The method further comprises the device, upon receipt of validation, removing the call from the hold state; and enabling at least one of voice and video functionality for the parties. The method further comprises the wireless communication device sending the request for validation to a telecommunications server and the server conducting real time monitoring of the call. The method further comprises the device continuously recording the call.

Abstract: Disclosed implementations use automated transcription and intent detection and an AI model to evaluate interactions between an agent and a customer within a call center environment. The evaluation flow used for manual evaluations is leveraged so that the evaluators can correct the AI evaluations when appropriate. Based on such corrections, the AI model can be retrained to accommodate specifics of the business and center—resulting in more confidence in the AI model over time.

Abstract: A device receives, from a user device, a communication associated with a support issue encountered by a user of the user device and assigns the communication to a position in a support queue based on when the communication is received, wherein the support queue includes data identifying positions of other communications received from other users, and data identifying when the other communications were received. The device processes data identifying the communication and historical communication data describing prior communications associated with the user, with a model, to determine an average time spent on hold by the user for the prior communications. The device modifies the position of the communication in the support queue based on the average time and performs one or more actions based on modifying the position of the communication in the support queue.

Abstract: The present invention relates to systems and methods for network labeling in order to enhance real time data transfers. A network for a real time data transfer is identified and predictive models for network performance are compared against to determine if the network is suitable for the data transfer. If so, then the real time data transfer may be completed as expected. However, if the network is predicted to be unsuitable for transmission an alternate means for connection may be suggested. The alternate suggestion may include delaying the data transfer until the network is expected to be in better conditions, connecting to another access point in the network, or switching to another network entirely. During the data transfer, the quality of the network is monitored in order to update the predictive models for the network's quality. Identifiers for the network may be utilized to keep track of the networks.

Abstract: Disclosed embodiments may relate to systems and methods for monitoring and/or mapping noise data from a plurality of noise monitoring devices. In some embodiments, the plurality of noise monitoring devices may include hearing protection devices configured to detect noise, and typically may communicate such noise data (which may also include location) so that the noise data can be pooled. The pooled noise data from the plurality of noise monitoring devices may then be used to the benefit of one or more of such noise monitoring devices.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for scheduling a call to be automatically initiated between users. The program and method provide for receiving, from a first device associated with a first user, a request for a call to be automatically initiated, at a scheduled time, between the first device and a second device corresponding to a second user; providing, to the second device and in response to the receiving, an invitation to participate in the call; receiving, from the second device and in response to the providing, an acceptance of the invitation; and providing for automatically initiating the call between the first device and the second device at the scheduled time.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprising an analytic server that automates training dataset generation for different application areas. The server may perform an automated, iterative refinement process to build a collection of dataset generator models over time. The server may receive a set of seed examples in a domain and generate candidate examples based on the features of the seed examples using data synthesis techniques. The server may execute a pre-trained label discriminator (LD) and domain discriminator (D2) on the candidate examples. The LD may identify and reject mislabeled data. The D2 may identify and reject out of domain data. The analytic server may regenerate new labeled data based on the feedback of the LD and D2. The analytic server may train a dataset generator by iteratively performing these steps for refinement until the regenerated candidate examples reach a pass rate threshold.

Abstract: Described is a system for continual learning using experience replay. In operation, the system receives a plurality of tasks sequentially, from which a current task is fed to an encoder. The current task has data points associated with the current task. The encoder then maps the data points into an embedding space, which reflects the data points as discriminative features. A decoder then generates pseudo-data points from the discriminative features, which are provided back to the encoder. The discriminative features are updated in the embedding space based on the pseudo-data points. The encoder then learns (updates) a classification of a new task by matching the new task with the discriminative features in the embedding space.

Abstract: A system for authenticating the calling device used to place a call to an enterprise call center. The system uses a premise component, a cloud-based Call Authentication Service (CAS), and orchestration between these two components. The premise component includes a number of sub-components including servers and probes. The CAS includes a Decision Engine that utilizes a number and variety of authentication plugins. The disclosed system may be used independently or as part of a multi-factor authentication strategy with other techniques such as reduced Knowledge-Based Authentication or voice biometrics.

Abstract: Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a contact center system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a plurality of contacts available for connection to an agent; determining, by the at least one computer processor, a plurality of preferred contact-agent pairings among possible pairings between the agent and the plurality of contacts; selecting, by the at least one computer processor, one of the plurality of preferred contact-agent pairings according to a probabilistic network flow model; and outputting, by the at least one computer processor, the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.

Abstract: 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.

Abstract: The present application describes providing an attestation level to a received communication. The attestation level may be used to communicate a level of security to a network or a called party that receives the communication. The attestation level associated with the communication may indicate to a destination network and/or recipient that the phone number associated with the communication is secure and/or the telephone number has not been spoofed.

Abstract: Systems and methods may be used to determine a fit for a hearing assistance device shell model. For example, a method may include receiving an image of anatomy of a patient including at least a portion of a canal aperture of an ear of the patient, generating a patient model of a portion of the anatomy of the patient, the patient model indicating at least one of a height or width of the canal aperture, and determining, using the patient model, a best fit model from a set of hearing assistance device shell models generated using a machine learning technique. The method may include outputting an identification of the best fit model.

Abstract: In some implementations, a cloud computing system that executes a function may receive an indication of an electronic communication to occur between a customer and an agent. The cloud computing system that executes the function may determine a classification of the electronic communication based on a first set of rules stored in a database of the cloud computing system and attributes associated with the electronic communication. The cloud computing system that executes the function may select, based on the classification of the electronic communication, a target queue from a plurality of potential queues to be associated with the electronic communication based on a second set of rules stored in the database. The cloud computing system that executes the function may select the agent from a plurality of potential agents for the electronic communication based on an association between the agent and the target queue.

Abstract: A method of providing artificial intelligence (AI) functionality to target legacy customer outreach platforms of a plurality of tenant enterprises includes storing a plurality of AI templates, each of which is associated with one or more AI routines, generating a campaign object associating one or more of the AI templates with a tenant enterprise from among the plurality of tenant enterprises, transforming a communication on a switching network associated with the tenant enterprise according to the one or more AI templates associated with the campaign object, and providing the transformed communication to a target legacy customer outreach platform of the tenant enterprise.

Abstract: A contact center, system, and method of operating a contact center are provided. In one example, the system includes a quantum computing resource and a server. The server is configured to receive a contact from a customer communication device, provide information about the contact to the quantum computing resource, receive a probabilistic output from the quantum computing resource based on the quantum computing resource processing the information about the contact, and make a work assignment decision for the contact based on the probabilistic output.

Abstract: A system and method for providing customer-support services to a user of a website through a web widget. When the user accesses a web page containing the web widget, a call is automatically made from the web widget to a customer-support system. In response to the call, the system obtains status information from the customer-support system indicating whether customer-support agents are available to take telephone phone calls. If the status information indicates customer-support agents are available to take telephone calls, the web widget provides a call-related interface to the user, wherein the call-related interface is configured to facilitate a telephone call with a customer-support agent. If the status information indicates customer-support agents are not available to take telephone calls, the web widget provides a non-call-related interface to the user, wherein the non-call-related interface is configured to facilitate an alternative channel of customer support that does not involve a telephone call.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes, in response to receipt at a call center of a call by a caller, generating a compatibility score for the caller, the compatibility score for the caller optimizes for caller satisfaction and potential upsell opportunities. The method also includes generating a compatibility score for individual agents available to handle the call, the compatibility score for the individual agents optimize for caller satisfaction and potential upsell opportunities. The method also includes matching the compatibility score for the caller to the compatibility scores for the individual agents and assigning an agent to the call based on the matching of the compatibility scores for the caller and the individual agents.