A computer-implemented method and system for enhancing interaction between a customer and a customer service representative of a company. D related to the customer is stored and received at a computer operated by the company, wherein the data can include a customer name, a customer address and a customer number. A telephonic interaction is preferably commenced between the customer and the customer service representative and a Web session is preferably commenced on a Web site for a client computer of the customer service representative. At least a part of the data is displayed on a workstation of the customer service representative as a first Web page, wherein the first Web page includes at least one selectable link to a second Web page. At least one selectable link is selected by the customer service representative to display the second Web page.

A process is described for a call management system to provide a call transcription supervisory monitoring interactive dashboard of incoming calls at a command center. A plurality of incoming calls are received including a first call reflecting a first incident and a second call reflecting a second incident. Audio from the first and second calls are transcribed. First and second incoming call objects are displayed in a call-by-call portion of the interactive dashboard. The transcripts are cross-referenced with a call-by-call keyword database to identify call-by-call keywords of interest, and the incoming call objects are populated with the call-by-call keywords of interest. An all-call object is displayed in an all-call portion of the interactive dashboard. The transcripts are cross-referenced with an all-call keyword database to identify all-call keywords of interest, and the all-call object is populated with the all-call keywords of interest.

A method and system matching experts or potential experts with an agent request for an expert are disclosed. Exemplary systems include an expert term extraction engine, an agent term extraction engine, and a matching engine to compare agent request terms to the expert terms from the expert term extraction engine and to determine whether there is a match or a potential match between the agent request terms and the extracted expert terms.

A method and apparatus for providing emergency assistance includes receiving audio, visual, or text data about an ongoing emergency at a public safety answering point, comparing that data to a database of other emergencies with an artificial intelligence engine, recognizing patterns in aggregated and correlated data by the artificial intelligence engine, and generating appropriate audio, visual, and text output for a human operator to respond to the emergency. An AI engine receives audio data, visual data, and text data related to ongoing emergencies being received at public safety answering points and compares it with data from other emergencies. The AI engine identifies key words and patterns and generates appropriate messages for operators. The system continuously generates feedback to the AI engine to aid in machine learning. The feedback includes: “the message was correct; continue drawing this conclusion”; and “the message was wrong; do not continue drawing this conclusion.”

Systems and methods are disclosed for generating a dynamic customized script to facilitate communication between a user and a service provider. The method includes receiving, via an interactive voice response (IVR) system, a request from a mobile device associated with at least one user. The contextual information associated with at least one user is processed, in real-time, based, at least in part, on the request. A dynamic customized script specific to the request is generated, in real-time, based, at least in part, on the processing of the contextual information. The request is routed, via the IVR system, to an agent from a pool of agents of the service provider. A presentation of the dynamic customized script is generated in a user interface of a device associated with the agent, wherein the dynamic customized script is step-by-step guidance to the agent for handling the request of at least one user.

Method for real-time automated call summarization comprises determining an issue of a caller based on at least one of a call transcript, an extracted intent from the call transcript, or a slot of the intent. Based on the issue, a resolution is determined, and further an action item to implement the resolution is determined. The determined resolution and the action item are displayed in a graphical user interface (GUI).

Systems and methods for executing a robotic process automation (RPA) workflow are provided. The RPA workflow is executed by a first robot. The execution of the RPA workflow is suspended by the first robot. A current context of the RPA workflow is serialized at a time of the suspension and the current context of the RPA workflow is stored. The execution of the RPA workflow is resumed by a second robot based on a triggering condition by retrieving the current context of the RPA workflow. The first robot and the second robot may be the same robot or different robots.

A method and system matching contact center agents and back office staff with a customer inquiry. Exemplary systems include an expert term extraction engine, a customer term extraction engine, and a matching engine to compare customer request terms to the expert terms from the customer term extraction engine. The comparison determines whether there is a match or potential match between the customer request terms and the stored expert terms. An exemplary system may also include a timer that communicates with one or more communication servers. Back office staff may assist contact center agents when one or more conditions are met, such as when a customer wait time exceeds a predetermined period or when there is no match or potential match between the customer request terms and the stored expert terms for contact center agents.

Systems and methods for executing a robotic process automation (RPA) workflow are provided. The RPA workflow is executed by a first robot. The execution of the RPA workflow is suspended by the first robot. A current context of the RPA workflow is serialized at a time of the suspension and the current context of the RPA workflow is stored. The execution of the RPA workflow is resumed by a second robot based on a triggering condition by retrieving the current context of the RPA workflow. The first robot and the second robot may be the same robot or different robots.

A dialogue device of a dialogue system relating to provision of a response to an inquiry from a user terminal includes an input unit that acquires the inquiry from the user terminal, a transmission unit that connects the user terminal and an operator terminal responding to the inquiry in accordance with the inquiry, an output unit that outputs questions for ascertaining details of the inquiry to the user terminal before connection made by the transmission unit, and a determination unit that determines a mode of the questions made by the output unit in accordance with an operating status of the operator terminal that can respond to the inquiry.