The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Sep. 26, 2023
Filed:
Nov. 11, 2019
Salesforce.com, Inc., San Francisco, CA (US);
Michael Machado, Burlingame, CA (US);
James Douglas Harrison, Mill Valley, CA (US);
Caiming Xiong, Menlo Park, CA (US);
Xinyi Yang, San Francisco, CA (US);
Thomas Archie Cook, Boulder, CO (US);
Roojuta Lalani, Fremont, CA (US);
Jean-Marc Soumet, San Jose, CA (US);
Karl Ryszard Skucha, Los Altos, CA (US);
Juan Rodriguez, Mountain View, CA (US);
Manju Vijayakumar, Pleasanton, CA (US);
Vishal Motwani, Palo Alto, CA (US);
Tian Xie, Palo Alto, CA (US);
Bryan McCann, Menlo Park, CA (US);
Nitish Shirish Keskar, San Francisco, CA (US);
Zhihao Zou, Foster City, CA (US);
Chitra Gulabrani, Palo Alto, CA (US);
Minal Khodani, Foster City, CA (US);
Adarsha Badarinath, Fremont, CA (US);
Rohiniben Thakar, Newark, CA (US);
Srikanth Kollu, Pleasanton, CA (US);
Kevin Schoen, Bothell, WA (US);
Qiong Liu, Cupertino, CA (US);
Amit Hetawal, San Ramon, CA (US);
Kevin Zhang, San Francisco, CA (US);
Kevin Zhang, Alameda, CA (US);
Johnson Liu, Santa Clara, CA (US);
Rafael Amsili, Mountain View, CA (US);
Salesforce, Inc., San Francisco, CA (US);
Abstract
A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.