Real-time agent assist

Patent metadata

Field	Value
Publication number	US-12095949-B2
Application number	US-202117564708-A
Country	US
Kind code	B2
Filing date	Dec 29, 2021
Priority date	Dec 29, 2021
Publication date	Sep 17, 2024
Grant date	Sep 17, 2024

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.

First claim

What is claimed is:

1. A system for real-time agent assist in a crisis scenario, the system comprising:
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 to determine (i) a confidence value indicative of a confidence that the knowledge fragment corresponds with the crisis scenario, (ii) a veracity value indicative of a veracity of the knowledge fragment, (iii) a frequency value indicative of a rate at which the knowledge fragment has been referenced over a period of time, and (iv) a proximity value indicative of a physical proximity of the contact center client 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;
wherein the crisis knowledge base is created ad hoc in response to a determination of an existence of the crisis scenario.

2. The system of claim 1 , wherein to analyze the knowledge fragment based on the crisis knowledge base comprises to analyze the knowledge fragment using an artificial intelligence system.

3. The system of claim 1 , wherein to receive the information from the contact center client comprises to receive the information with a chatbot.

4. The system of claim 1 , further comprising a contact center system, wherein the contact center system comprises the at least one processor and the at least one memory.

5. A method for real-time agent assist in a crisis scenario, the method comprising:
receiving, by a contact center system, an information request from a contact center client;
evaluating, by the contact center system, the information request using natural language understanding to determine a knowledge fragment associated with the information request;
analyzing, by the contact center system, the knowledge fragment based on a crisis knowledge base of the contact center system to determine (i) a confidence value indicative of a confidence that the knowledge fragment corresponds with the crisis scenario, (ii) a veracity value indicative of a veracity of the knowledge fragment, (iii) a frequency value indicative of a rate at which the knowledge fragment has been referenced over a period of time, and (iv) a proximity value indicative of a physical proximity of the contact center client to the crisis scenario; and
generating, by the contact center system, a response to the contact center client in response to analyzing the knowledge fragment based on the crisis knowledge base;
wherein the crisis knowledge base is created ad hoc in response to determining an existence of the crisis scenario.

6. The method of claim 5 , wherein the crisis scenario involves at least one of a humanitarian crisis or an enterprise crisis.

7. The method of claim 5 , further comprising interrogating the contact center client regarding one or more characteristics of the knowledge fragment.

8. The method of claim 7 , further comprising updating the crisis knowledge base in response to interrogating the contact center client regarding the one or more characteristics of the knowledge fragment.

9. The method of claim 5 , wherein analyzing the knowledge fragment based on the crisis knowledge base comprises analyzing the knowledge fragment using an artificial intelligence system.

10. A method for real-time agent assist in a crisis scenario, the method comprising:
receiving, by a contact center system, an information request from a contact center client during a contact center interaction;
evaluating, by the contact center system, the information request using natural language understanding to determine a knowledge fragment associated with the information request;
analyzing, by the contact center system during the contact center interaction, the knowledge fragment based on a crisis knowledge base of the contact center system to determine (i) a confidence value indicative of a confidence that the knowledge fragment corresponds with the crisis scenario, (ii) a veracity value indicative of a veracity of the knowledge fragment, (iii) a frequency value indicative of a rate at which the knowledge fragment has been referenced over a period of time, and (iv) a proximity value indicative of a physical proximity of the contact center client to the crisis scenario; and
generating, by the contact center system, a response to the contact center client in response to analyzing the knowledge fragment based on the crisis knowledge base;
wherein the crisis knowledge base is created ad hoc in response to a determination of an existence of the crisis scenario.

Assignees

• Genesys Cloud Services Inc

Inventors

• Te Booij Merijn
• Stoops Dan
• Bell Cliff

Classifications

• G06F40/30

  Semantic analysis · CPC title

• G06F40/279

  Recognition of textual entities · CPC title

• G06Q30/01

  Customer relationship services · CPC title

• G06Q50/265

  Personal security, identity or safety · CPC title

• H04M3/5116 Primary

  for emergency applications · CPC title