Intelligent oversight of multi-party engagements

Patent metadata

Field	Value
Publication number	US-12530615-B2
Application number	US-202117352899-A
Country	US
Kind code	B2
Filing date	Jun 21, 2021
Priority date	Jun 21, 2021
Publication date	Jan 20, 2026
Grant date	Jan 20, 2026

Abstract

Artificial intelligence (AI) oversight may be added to a multiparty engagement, such as a conference between devices having user interfaces. The AI may apply visual indicators, e.g., informational elements, recommendations, or other data, on one or more user interface. Visual indicators assist with presenting or participating in a conference. Visual indicators may highlight, e.g., AI-determined attributes of participants in the conference. Attributes may be derived physiological characteristics of participants, such as mood, apparent interest, paying attention, as well as AI-derived data from analyzing data sources, such as data about the participant, past engagements, time zone, name/title and other information to facilitate interaction with the participant. The AI may also review data for past deals, resume, project plans, social media, customer relationship manager data, and the like and develop models to allow it to monitor a conference and provide recommendations to facilitate conference goals.

First claim

What is claimed is:

1 . A computer system in a conference with other computer systems used by participants to a conference, the computer system configured to communicate with a host system to provide an artificial intelligence analysis of at least a key participant to the conference, the computer system comprising a set of one or more processors, and a memory coupled to the one or more processors for storing instructions that when executed by the one or more processors cause the computer system to perform operations comprising:
receive, from the host system, the artificial intelligence analysis of at least the key participant; cause display of an interface for the conference, the interface including portions associated with at least one other computer system in the conference; cause overlay of the portions of the interface with one or more visual representations of meta-data associated with the at least one other computer system, the meta-data including at least a portion of the received artificial intelligence analysis; determine a recommendation based at least in part on the received artificial intelligence analysis; validate the recommendation against corporate policy rules; cause display in the interface the recommendation based at least in part on the received artificial intelligence analysis according to a result of validating the recommendation; determining a history of activity for the conference; identifying a current goal for a current conference segment based at least in part on the history of activity, wherein identifying the current goal is performed using a relationship manager source, the relationship manager source including information identifying one or more of: a customer, lead, or deal; comparing a current activity in the current conference segment to the current goal; evaluating the current activity to determine if it achieves the current goal; and determining the recommendation based at least in part on the evaluation of the current activity.

2 . The computer system of claim 1 , in which the conference has one or more stages, and the memory including further instructions to cause the computer system to perform operations comprising:
identify an attendance for a current stage in the conference; update the key participant based at least in part on the attendance; and determine a next stage for the multi-stage conference based at least in part on the artificial intelligence analysis of an activity of at least the key participant in the current stage.

3 . The computer system of claim 2 , the memory including further instructions to cause the computer system to perform operations comprising:
identifying a required participant for the current stage; and determining the next stage based at least in part on whether the required participant is in attendance.

4 . The computer system of claim 1 , wherein the computer systems include a server to perform the invoking the machine learning model to monitor the conference and to determine the artificial intelligence analysis.

5 . The computer system of claim 1 , wherein:
the artificial intelligence analysis includes an engagement factor determined for at least the key participant; and the memory including further instructions to causing the computer system to perform operations comprising cause display of an alert in the interface based at least in part on the engagement factor.

6 . The computer system of claim 1 , the memory including further instructions to cause the computer system to perform operations comprising:
monitoring a selected one or more of speech, physiology, physical motion, or history associated with one or more participants in the conference to determine an activity of the one or more participant; and determining the recommendation based at least in part on the monitoring.

7 . The computer system of claim 1 , the memory including further instructions to cause the computer system to perform operations comprising:
inspecting an organizational hierarchy to determine a first metric; evaluating a calendar invitation to determine a second metric; lookup a social media content to determine a third metric; rank selected ones of the participants based at least in part on the first, second and third metric; and determine the key participant based at least in part on the rank.

8 . The computer system of claim 1 , in which a relationship management system tracks the one or more segment, the memory including further instructions to cause the computer system to perform operations comprising:
lookup data corresponding to a tracking of the one or more segment in the relationship management system; and determine the history of activity based at least in part on the data.

9 . A method to establish a conference with remote computer systems executing a conference application for respective participants of the conference, and engage in the conference based at least in part on receiving, from a host to be configured to invoke a machine learning model to monitor the conference, an artificial intelligence analysis of at least a key participant to the conference, the conference having one or more stages, the method comprising:
receive the artificial intelligence analysis of at least the key participant; cause display of an interface for the conference, the interface including portions associated with at least one other computer system in the conference; cause overlay of the portions of the interface with one or more visual representations of meta-data associated with the at least one other computer system, the meta-data including the received artificial intelligence analysis; determine a recommendation based at least in part on the received artificial intelligence analysis; validate the recommendation against corporate policy rules; cause display in the interface the recommendation according to a result of validating the recommendation; identify an attendance for a current stage in the conference; update the key participant based at least in part on the attendance; and determine a next stage for the conference based at least in part on the artificial intelligence analysis of an activity of at least the key participant in the current stage.

10 . The method of claim 9 , further comprising:
identify a required participant for the current stage; and determine the next stage based at least in part on whether the required participant is in attendance.

11 . The method of claim 9 , wherein the computer system to receive the artificial intelligence analysis is to provide an artificial intelligence service.

12 . The method of claim 9 , in which the artificial intelligence analysis includes an engagement factor determined for at least the key participant, the method further comprising:
cause display of an alert in the interface based at least in part on the engagement factor.

13 . The method of claim 9 , further comprising:
determine an activity of the one or more participant based at least in part on monitor a selected one or more of speech, physiology, physical motion, or history associated of one or more participants in the conference; and determine the recommendation based at least in part on the determined activity.

14 . The method of claim 9 , further comprising:
inspect an organizational hierarchy to determine a first metric; evaluate a calendar invitation to determine a second metric; lookup a social media content to determine a third metric; rank selected ones of the participants based at least in part on the first, second and third metric; and determine the key participant based at least in p

Assignees

• Salesforce Inc

Inventors

• Harrison Daniel Thomas

Classifications

• G06N5/04

  Inference or reasoning models · CPC title

• G06Q10/0639

  Performance analysis of employees; Performance analysis of enterprise or organisation operations · CPC title

• G06Q10/0633 Primary

  Workflow analysis · CPC title

• G06N5/022

  Knowledge engineering; Knowledge acquisition · CPC title

• G06N3/08

  Learning methods · CPC title