Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

A system for automatic authentication of service requests includes authentication of a remote access device. This authentication may be accomplished automatically prior to text or audio communication between a customer and a service agent. In some embodiments, authentication is accomplished automatically by authentication of the remote access device or accomplished by asking the customer questions. A single authentication of the remote access device may be used to authenticate a service request transferred between service agents. The authentication of the remote device may include, for example, use of a personal identification number, a fingerprint, a photograph, and/or a hardware identifier. Some embodiments include an intelligent pipeline configured for managing queues of customer service requests.

The number of agents to which incoming queries to a customer interaction center agent group may be distributed is limited based on skip criteria. The skip criteria is defined based on information associated with agent devices, such as locked status of a device, in-memory status of a client application at the device, or whether a telephone number provisioned for use with the device is from an external public switched telephone network. Agents which fail to satisfy the skip criteria are excluded from distributions of queries to improve wait times for customer interaction center users. Thus, queries are distributed from a queue to agents which satisfy the skip criteria.

A contact center system correlates one or more past user interactions to a current user interaction with the contact center system. The current user interaction may in some cases use a different communication modality (e.g., chat, voice, video, SMS, email, or social) than a past user interaction. The contact center system may automatically alert a supervisor agent when the system detects that a certain user warrants more attention. Real-time assistance may be provided to an agent of the contact center system based on aggregated data from a user's history of user interactions across modalities.

Traditionally, when a feature is updated or a new feature is released, the feature undergoes internal testing and validation before external distribution. However, some features may receive proportionately less internal usage than customer usage reflected externally. Low internal usage of features can lead to weak telemetry data, which can allow code regressions (e.g., bugs) to go undetected until the features are released to customers. Accordingly, accelerated internal feature usage is provided to mirror external customer usage. Highly used features are dynamically identified and, any deficiencies in internal feature usage are identified. Tenant sites estimated to generate at least a portion of the deficiency in feature usage are identified. These sites may be migrated or replicated to internal validation rings to generate additional internal feature usage. By increasing internal testing and validation, the stability and reliability of feature releases are increased, thereby improving customer experience and satisfaction with the software product.

Machine learning technology can analyze in real-time the data from a call between a person and a customer service representative. Based on this analysis, a server can determine a sentiment score that describes a sentiment expressed by the person or the customer service representative. If the server determines that the sentiment score is less than or equal to a pre-determined value, the server can inform the customer service representative's manager so that the manager can take further action to help the person and/or the customer service representative.

Aspects of call routing based on technical skills of users are discussed. Responses to a set of questions posed to a user are received to assess a technical skill level of the user. The user may be categorized in a category from among a plurality of categories based on the technical skill level and a decision may be provided to a route a call from the user to one of a human agent and a virtual agent based on the categorization.

Techniques for behavioral pairing in a task assignment system are described. 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.

The present disclosure can include a system, method, or platform for automated call management utilizing a switch capable being utilized with signals from a communication device. The switch interfaces with an artificial intelligence engine that provides contextual interactions to the switch. One or more databases of playback assets may be utilized to send the playback messages to the communications device. Middleware may provide analysis of data coming into the switch along with a call engine for configuring one or more calls made through the switch. Each call can include a call detail record (CDR) which is updateable with information regarding the calls.

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 deice status data to identify potential faults that may affect mobile device functionality. A corresponding system, apparatus, and computer program product are also provided.