Avaya Inc.

Gerard Carty

Thomas J Moran

Contact center agents commonly have dissimilar levels of skill for a particular topic or ability. Often an expert is available to help lesser-skilled agents, but such experts may not always be available. Automated systems and methods are provided that allow for an agent-customer interaction to be monitored and, when a question is present, identify a best-matching knowledge unit to address the question. With the knowledge unit identified, a prior communication portion associated with the knowledge unit is then presented to the agent, such as via pop-up message, whisper voice message, etc., to allow the agent to have the benefit of the knowledge of the expert to answer the question without engaging the expert.

Automatic message generation and presentation to a communication node engaged in a communication

A video stream of a video call between a communication endpoint of customer and a communication endpoint of a contact center agent is received. The video stream of the video call is processed in real-time to generate a real-time emotion transcript. The real-time emotion transcript tracks a plurality of separate emotions based on non-verbal expressions (e.g. facial expressions) that occur in the video stream of the video call. For example, different emotions of both the customer and the contact center agent may tracked in the real-time emotion transcript. The real-time emotion transcript is compared to an emotion transcript of at least one previous video call to determine if the video call should be handled differently in the contact center. In response to determining that video call should be handled differently in the contact center, an action determined to change how the video call is managed in the contact center.

Video call routing and management based on artificial intelligence determined facial emotion

A plurality of nodes on a network may be utilized to communicate with external nodes outside of the plurality. The removal from service of a number of the plurality of nodes may cause the network to become ineffective or inoperable. Nodes may be monitored to determine a predicated out-of-service condition and mitigating actions taken. For example, if an operator of a node is likely to be unable to provide required inputs to the node, another node with associated operator may be allocated to become available at a timely predicted to coincide with the outage of the monitored node. Other mitigating actions may also be utilized, such as reassigning the physical location of the monitored node.

Predictive network node allocation

A process for updating a second agent about a call in a contact center comprises receiving a call at the contact center and connecting the call to a device associated with a first agent of the contact center. A processor is used to configure a list of keywords to detect during the call, and when a key word is detected (e.g., using a speech analyzer), a snippet of the call based on the detected keywords is identified. The snippets are presented to a second agent through a device associated with the second agent. The call is then connected to the device associated with the second agent.

Real-time speech feed to agent greeting

A system for providing Payment Card Industry (PCI) compliance for a contact center is disclosed. The system includes a monitoring module configured to monitor a communication session between an agent and a customer. At least one image associated with the agent's computer screen is captured during the communication session. An analysis module is configured to compare the at least one image with at least one predefined image. A control module is configured to control a recording of information associated with the communication session based on the comparison.

System and method for payment card industry compliance

A contact center, communication system, and method are disclosed. An illustrative contact center includes a conversational analysis engine that is applied to media exchanged between a customer and a first agent during a first interaction and determines a context of the first interaction. The illustrative contact center further includes a repository of greetings for a second agent and a greeting from the repository of greetings for the second agent is selectable based on the determined context of the first interaction. The illustrative contact center further includes a network interface that facilitates a presentation of the selected greeting to the customer when the customer is transferred from the first agent to the second agent.

Dynamic agent greeting based on prior call analysis

A process for updating a second agent about a call in a contact center comprises receiving a call at the contact center and connecting the call to a device associated with a first agent of the contact center. A processor is used to configure a list of keywords to detect during the call, and when a key word is detected (e.g., using a speech analyzer), a snippet of the call based on the detected keywords is identified. The snippets are ordered and presented to a second agent through a device associated with the second agent. The call is then connected to the device associated with the second agent.

Managing resources in a contact center including assigning each resource to one of a first set of resources each comprising a proficiency level above a first threshold for a first resource attribute, or a second set of resources each comprising a proficiency level below the first threshold for the first resource attribute and a proficiency level above a second threshold for a second resource attribute. An expected number of contacts requiring resources possessing one of the first or second resource attribute is predicted for a time period, and a correlation between the first and second resource attribute is identified. Based on the correlation, a minimum number of resources from each set required to handle the expected number of contacts at a predetermined service level for the time period is forecasted. The minimum number of resources from the first set is less than a number of resources required without the correlation.

Systems and methods for optimal scheduling of resources in a contact center

Embodiments provide an oversight mechanism using eye tracking to monitor a human agent's review of artificial intelligence generated contact in a contact center communication session. Content generated by an artificial intelligence engine for each session can be presented to the human agent through a user interface for review by the human agent. While the generated content is being presented, an eye tracking system associated can monitor review of the generated content by the human agent. An indication of the human agent's level of attention to the generated content can be generated based on monitoring the review of the content by the human agent. The indication of the human agent's level of attention can be stored in a set of Key Performance Indicators (KPIs) for the human agent. One or more reports can be provided based on the KPIs.

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Galway, Ireland

Gerard Carty