Abstract: The present invention allows a CEC system to automatedly track the use, storage, access, and modification of sensitive information/data in the system through desktop monitoring. Further, through desktop, video, and audio monitoring of CSRs the system can automatedly determine the improper use, access, storage, and modification of sensitive information by implementing sensitive data use rules that allow a system to be specialized for the user. Finally, the system can automatedly determine and implement violation actions for the improper use, storage, access, and manipulation of sensitive information. This provides an intelligent system capable of locating all sensitive data in the system and regulating the use, access, and storage of sensitive data in the system.

Abstract: A system for generating wrap-up information is capable of learning how interactions are transformed into contact notes and outcome codes using natural language processing and can generate the contact notes and outcome codes for new incoming interactions by applying prediction models trained on interaction data, contact notes and outcome codes. The system for generating wrap-up information receives interaction data, including interaction audio data, interaction transcripts, associated contact notes and associated outcome codes. The interaction transcripts are generated from the previous interactions between agents and customers. The contact notes and outcome codes are generated by agents during the associated previous interactions. The system processes and uses the interaction data to train prediction models to analyze interaction audio data and interaction transcripts and predict appropriate contact notes and outcome codes for the interaction.

Abstract: An artificial intelligence (AI) application uses an external machine learning component from a different computing environment to develop context data for use by the AI application. The context data includes raw data outputs from the external machine learning component. An active machine learning component is executed with the context data and provides a suggested next step to a computer to implement as an automated output. A feedback loop adds the suggested next step from the active machine learning component to the context data and forms an augmented data set for providing context to the AI application. A context component selects a rule from a rules engine that corresponds to the augmented data set. The computer implements an automated output according to the rule that was selected.

Abstract: The present invention allows a CEC system to automatedly track the use, storage, access, and modification of sensitive information/data in the system through desktop monitoring. Further, through desktop, video, and audio monitoring of CSRs the system can automatedly determine the improper use, access, storage, and modification of sensitive information by implementing sensitive data use rules that allow a system to be specialized for the user. Finally, the system can automatedly determine and implement violation actions for the improper use, storage, access, and manipulation of sensitive information. This provides an intelligent system capable of locating all sensitive data in the system and regulating the use, access, and storage of sensitive data in the system.

Abstract: The present invention is a method and system for automatically producing a form. Upon receiving at least one type of data input, the system analyzes the data input and produces a form based on the results of the analysis of the data input. This process may be used to either generate or update a form, and may be repeated to update an existing form.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: The present system and method allow a customer service agent to preview an audio file of a customer's interaction with an interactive voice response (IVR) system before taking the call. While customer voice commands are typically used to navigate through an IVR system to reach an appropriate agent, the present system and method record the customer's voice commands in response to IVR prompts as an audio file and provide them to the agent before she or he takes the call. The agent may play the audio file on a customer engagement center desktop.

Abstract: The present system and method allow a customer service agent to preview an audio file of a customer's interaction with an interactive voice response (IVR) system before taking the call. While customer voice commands are typically used to navigate through an IVR system to reach an appropriate agent, the present system and method record the customer's voice commands in response to IVR prompts as an audio file and provide them to the agent before she or he takes the call. The agent may play the audio file on a customer engagement center desktop.

Abstract: The present system and method allow a customer service agent to preview an audio file of a customer's interaction with an interactive voice response (IVR) system before taking the call. While customer voice commands are typically used to navigate through an IVR system to reach an appropriate agent, the present system and method record the customer's voice commands in response to IVR prompts as an audio file and provide them to the agent before she or he takes the call. The agent may play the audio file on a customer engagement center desktop.