Abstract: A system for generating outbound video using generative artificial intelligence and machine learning according to an embodiment includes retrieving, by a computing system, a plurality of attributes of a target video recipient for each of a plurality of target video recipients, wherein each attribute of the plurality of attributes is indicative of a preference or characteristic of the respective target video recipient, generating, by the computing system, a customized outbound video message for each of the plurality of target video recipients using a generative artificial intelligence system based on the plurality of attributes for the respective target video recipient and at least one artificial intelligence model, and transmitting, by the computing system, each customized outbound video message to the respective target video recipient in response to generating the customized outbound video message for each of the plurality of target video recipients.

Abstract: A method for agent training using generative artificial intelligence and machine learning according to an embodiment includes retrieving, by a computing system, original training content for contact center agents, analyzing, by the computing system, the original training content using machine learning based on agent characteristics of a particular agent to determine target content characteristics for training content customized to the particular agent, generating, by the computing system, custom agent training content using a generative artificial intelligence system based on the original training content and the target content characteristics, providing, by the computing system, a virtual training session for the particular agent using the generated custom agent training content, receiving, by the computing system, results data associated with the particular agent’s completion of the virtual training session, and updating, by the computing system, an artificial intelligence model leveraged by the machine lea

Abstract: A method for contact center agent incentivization via automated gamification according to an embodiment includes transferring an interaction between a contact center agent and a user to an automated agent, prompting, by the automated agent, the user to reward the contact center agent based on the interaction between the user and the contact center agent, receiving a selection of a reward option made by the user in response to prompting the user to reward the contact center agent, determining a point value associated with the user's selected reward option based on a mapping table, and associating the user's selected reward option with the contact center agent in an agent rewards table.

Abstract: A method according to an embodiment includes determining a group of subject matter experts in a back office with expertise to address a question from a user of a contact center system, determining an availability of one or more of the subject matter experts via a back-office platform executed by corresponding back-office devices of the one or more subject matter experts, assigning, via the back-office platform, a communication token to a selected subject matter expert determined to be available, wherein the communication token is associated with the question from the user, monitoring, via the back-office platform, for updates to the back-office platform associated with the communication token, receiving an update from the back-office platform associated with the communication token, and transmitting, via the contact center system, a message to the user device based on an update to the communication token.

Abstract: A method for analysis of in-person attendant interactions according to an embodiment includes determining a location of a person within a monitored area based on sensor data generated by one or more sensors, determining a start queue time associated with a time at which the person is located at a start queue position within the monitored area, determining an end queue time associated with a time at which the person is located at an end queue position, recording interaction data of an interaction between the person and an attendant when the person is located at the end queue position, determining a wait time of the person in the queue based on the start queue time and the end queue time, determining an interaction time of the interaction based on the interaction data, and adjusting an attendant schedule for the monitored area to improve the wait time or the interaction time.

Abstract: A method for contact center agent incentivization via automated gamification according to an embodiment includes transferring an interaction between a contact center agent and a user to an automated agent, prompting, by the automated agent, the user to reward the contact center agent based on the interaction between the user and the contact center agent, receiving a selection of a reward option made by the user in response to prompting the user to reward the contact center agent, determining a point value associated with the user's selected reward option based on a mapping table, and associating the user's selected reward option with the contact center agent in an agent rewards table.

Abstract: A system for real-time agent assist in a crisis scenario according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to receive an information request from a contact center client, evaluate the information request using natural language understanding to determine a knowledge fragment associated with the information request, analyze the knowledge fragment based on a crisis knowledge base of the system with respect to at least one of a confidence in the knowledge fragment, a veracity of the knowledge fragment, a frequency of the knowledge fragment, or a proximity of the knowledge fragment to the crisis scenario, and generate a response to the contact center client in response to analysis of the knowledge fragment based on the crisis knowledge base.

Abstract: A method according to an embodiment includes determining a group of subject matter experts in a back office with expertise to address a question from a user of a contact center system, determining an availability of one or more of the subject matter experts via a back-office platform executed by corresponding back-office devices of the one or more subject matter experts, assigning, via the back-office platform, a communication token to a selected subject matter expert determined to be available, wherein the communication token is associated with the question from the user, monitoring, via the back-office platform, for updates to the back-office platform associated with the communication token, receiving an update from the back-office platform associated with the communication token, and transmitting, via the contact center system, a message to the user device based on an update to the communication token.

Abstract: A system for utilizing conversational artificial intelligence (AI) to train contact center agents according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored therein that, in response to execution by the at least one processor, causes the system to place a virtual call from an automated training system to an agent device of an agent, connect the virtual call to a chatbot in response to establishing a communication connection with the agent device, transmit one or more statements from the chatbot, receive, from the agent device, one or more agent responses of the agent corresponding to the one or more statements, and analyze the one or more agent responses to determine one or more training characteristics associated with AI-based contact center training of the agent.

Abstract: A system for real-time agent assist in a crisis scenario according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to receive an information request from a contact center client, evaluate the information request using natural language understanding to determine a knowledge fragment associated with the information request, analyze the knowledge fragment based on a crisis knowledge base of the system with respect to at least one of a confidence in the knowledge fragment, a veracity of the knowledge fragment, a frequency of the knowledge fragment, or a proximity of the knowledge fragment to the crisis scenario, and generate a response to the contact center client in response to analysis of the knowledge fragment based on the crisis knowledge base.

Abstract: A system for utilizing conversational artificial intelligence (AI) to train contact center agents according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored therein that, in response to execution by the at least one processor, causes the system to place a virtual call from an automated training system to an agent device of an agent, connect the virtual call to a chatbot in response to establishing a communication connection with the agent device, transmit one or more statements from the chatbot, receive, from the agent device, one or more agent responses of the agent corresponding to the one or more statements, and analyze the one or more agent responses to determine one or more training characteristics associated with AI-based contact center training of the agent.

Abstract: A system and method are presented for the re-authentication of asynchronous messaging, specifically within enterprise to consumer communications. A third-party enterprise messaging server may be used as a conduit for a messaging service allowing for customer interaction with a business. The messaging server can append a re-authentication process for customers once a customer has been authenticated by the enterprise. Each time a customer resumes an interaction exceeding a timeout threshold, the messaging server invokes its re-authentication process. Lapsed interactions may be treated as continuous without having the customer re-authenticate through the enterprise specific authentication.

Abstract: A method for orchestrating a chat interaction with a customer and multiple sources that includes providing an animation library that includes conversational states, graphic stills corresponding to respective ones of the conversational states, animation templates, and source-based modifications corresponding to respective ones of the multiple sources. The method may include generating a source-informative animation by: determining a source of a chat message; determining a conversational state for the chat message; selecting a graphic still for the message; selecting an animation template for the chat message based on the selected graphic still; selecting a source-based modification that corresponds to the source; and modifying the animation template pursuant to the source-based modification so to generate the source-informative animation. The method may include sending a signal to the customer configured to generate thereon a chat interface having the chat message and source-informative animation.

Abstract: A system, comprising includes an orchestration server including a processor, the orchestration server to receive authentication factors. A rules engine connects with the orchestration server, the orchestration to send the authentication factors to the rules engine and to request a decision on authentication from the rules engine. The rules engine to send the decision on authentication to the orchestration server based on the received authentication factors and a rules set.

Abstract: A system and method are presented for the re-authentication of asynchronous messaging, specifically within enterprise to consumer communications. A third-party enterprise messaging server may be used as a conduit for a messaging service allowing for customer interaction with a business. The messaging server can append a re-authentication process for customers once a customer has been authenticated by the enterprise. Each time a customer resumes an interaction exceeding a timeout threshold, the messaging server invokes its re-authentication process. Lapsed interactions may be treated as continuous without having the customer re-authenticate through the enterprise specific authentication.

Abstract: A system includes a contact center to provide an interaction between a customer and an agent workstation of the contact center. A contact center network connects a call from a mobile device to an interactive voice response application. A mobile engagement platform collect authentication information from the mobile device to authenticate a customer using the mobile device. A short message service platform sends a link to connect the mobile device to a mobile application. The mobile engagement server authenticates the customer of the mobile device for the mobile application based on the collected authentication information.

Abstract: A system and method include a customer engagement platform of an enterprise. The customer engagement platform is configured to connect with an audience computer and provide to the audience computer contact information associated with a marketing attribution. The marketing attribution accompanies an impression served to the audience computer. The impression and marketing attribution associated with the contact information are sent to the customer engagement platform during an interaction with the enterprise.

Abstract: A system, comprising includes an orchestration server including a processor, the orchestration server to receive authentication factors. A rules engine connects with the orchestration server, the orchestration to send the authentication factors to the rules engine and to request a decision on authentication from the rules engine. The rules engine to send the decision on authentication to the orchestration server based on the received authentication factors and a rules set.

Abstract: A system includes a contact center to provide an interaction between a customer and an agent workstation of the contact center. A contact center network connects a call from a mobile device to an interactive voice response application. A mobile engagement platform collect authentication information from the mobile device to authenticate a customer using the mobile device. A short message service platform sends a link to connect the mobile device to a mobile application. The mobile engagement server authenticates the customer of the mobile device for the mobile application based on the collected authentication information.

Abstract: A system, comprising includes an orchestration server including a processor, the orchestration server to receive authentication factors. A rules engine connects with the orchestration server, the orchestration to send the authentication factors to the rules engine and to request a decision on authentication from the rules engine. The rules engine to send the decision on authentication to the orchestration server based on the received authentication factors and a rules set.