AI Automated Facilitation of Support Agent/Client Interactions in Multi-Modal Communications

A process for artificial intelligence (AI), automated, real-time, facilitation of support interactions between an agent and a client in multi-modal communications comprising the steps of:

• initiating, over a voice channel in response to a request from the client, voice communications via an interactive voice response (IVR) system in which the client provides user identification and identifies an issue with which assistance is required;
• capturing, by an AI assistant, the voice communications;
• generating, by the AI assistant, a transcription of the voice communications on speech-to-text processing;
• determining, by the AI assistant from an initial context of the voice communications, the issue;
• retrieving, by server from secure storage, account information and user details for the client;
• generating, by a server and the AI assistant based on the initial context, the transcription, the issue, the account information, and the user details, a custom agent desktop graphical user interface (GUI) session for the agent to assist the client with the issue;
• initiating, by the server on a client device over a digital-data channel, digital communications in an app with the client;
• generating, by the AI assistant based on statements made by the agent on the voice channel, text representations of at least some of the statements in the digital communications;
• auto-populating, by the AI assistant, the issue in the app for verification;
• enabling, by the server and AI assistant, the client to verify the issue in the app via the digital channel;
• auto-populating, by the AI assistant, the account information in the app for verification;
• enabling by the server and the AI assistant, the client to verify the account information in the app via the digital channel;
• auto-populating, by the AI assistant, the user details in the app for verification;
• enabling by the server and the AI assistant, the client to verify user details via the digital channel;
• synchronizing, by the AI assistant, the voice communications and the digital communications;
• generating, by the AI assistant in real-time, an on-going session summary for actions taken during the support interactions;
• displaying, by the AI assistant in real-time on the client device, the on-going session summary so the client can follow along with the support interactions;
• providing, by the AI assistant in the custom agent desktop, a script for addressing the issue;
• analyzing, by the AI assistant, the voice communications and the digital communications in order to generate an on-going context for the support interaction;
• predicting, by the AI assistant based on the voice communications, the digital communications, and the on-going context, an ultimate problem to be solved and predictive suggestions to provide to the agent to make progress towards solving the ultimate problem;
• providing, by the AI assistant the predictive suggestions for the agent to consider as part of the support interaction;
• implementing, by the AI assistant, the predictive suggestions automatically if approved by the agent;
• continuously updating, based on monitored feedback from the voice communications, the digital communications, and the on-going context by the AI assistant, the predictive suggestions on an on-going basis to updated predicted suggestions and implementing the updated predictive suggestions when approved by the agent until the support interaction is successfully concluded;
• and
• learning, by the AI assistant from the voice communications, the digital communications, the on-going context, the predictive suggestions that were implemented and the updated predictive suggestions that were implemented in order to optimize the AI assistant to provide an optimum solution if presented with the issue in future.

A process for artificial intelligence (AI), automated, real-time, facilitation of support interactions between an agent and a client in multi-modal communications comprising the steps of:

• initiating, over a voice channel in response to a request from the client, voice communications via an interactive voice response (IVR) system in which the client provides user identification and identifies an issue with which assistance is required;
• capturing, by an AI assistant, the voice communications;
• extracting, by the AI assistant from the voice communications, a digital voice sample of the client for initial authentication;
• transmitting, from the AI assistant to a server, the digital voice sample;
• retrieving, by the server from secure storage, an authentic customer voice deposit;
• authenticating, by the AI assistant, the client by a comparison of the authentic customer voice deposit to the digital voice sample;
• generating, by the AI assistant, a transcription of the voice communications on speech-to-text processing;
• determining, by the AI assistant from an initial context of the voice communications, the issue;
• retrieving, by the server from secure storage, account information and user details for the client;
• generating, by a server and the AI assistant based on the initial context, the transcription, the issue, the account information, and the user details, a custom agent desktop graphical user interface (GUI) session for the agent to assist the client with the issue;
• initiating, by the server on a client device over a digital-data channel, digital communications in an app with the client;
• generating, by the AI assistant based on statements made by the agent on the voice channel, text representations of at least some of the statements in the digital communications;
• auto-populating, by the AI assistant, the issue in the app for verification;
• enabling, by the server and AI assistant, the client to verify the issue in the app via the digital channel;
• auto-populating, by the AI assistant, the account information in the app for verification;
• enabling by the server and the AI assistant, the client to verify the account information in the app via the digital channel;
• auto-populating, by the AI assistant, the user details in the app for verification;
• enabling by the server and the AI assistant, the client to verify user details via the digital channel;
• synchronizing, by the AI assistant, the voice communications and the digital communications;
• generating, by the AI assistant in real-time, an on-going session summary for actions taken during the support interactions;
• displaying, by the AI assistant in real-time on the client device, the on-going session summary so the client can follow along with the support interactions;
• providing, by the AI assistant in the custom agent desktop, a script for addressing the issue;
• analyzing, by the AI assistant, the voice communications and the digital communications in order to generate an on-going context for the support interaction;
• predicting, by the AI assistant based on the voice communications, the digital communications, and the on-going context, an ultimate problem to be solved and predictive suggestions to provide to the agent to make progress towards solving the ultimate problem;
• providing, by the AI assistant the predictive suggestions for the agent to consider as part of the support interaction;
• implementing, by the AI assistant, the predictive suggestions automatically if approved by the agent;
• continuously updating, based on monitored feedback from the voice communications, the digital communications, and the on-going context by the AI assistant, the predictive suggestions on an on-going basis to updated predicted suggestions and implementing the updated predictive suggestions when approved by the agent until the support interaction is successfully concluded;
• and
• learning, by the AI assistant from the voice communications, the digital communications, the on-going context, the predictive suggestions that were implemented and the updated predictive suggestions that were implemented in order to optimize the AI assistant to provide an optimum solution if presented with the issue in future.