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.

Date of Patent:
Dec. 02, 2025

Filed:

May. 02, 2025
Applicant:

Istari Digital, Inc., Charleston, SC (US);

Inventors:

William Roper, Jr., Charleston, SC (US);

Christopher Lee Benson, Arlington, VA (US);

Sriram Krishnan, Cambridge, MA (US);

Peter Galvin, Watertown, MA (US);

Pranav Sumanth Doijode, Rijswijk, NL;

Bayan Abedal-Muttaleb Afif Hashem, Amman, JO;

Assignee:

Istari Digital, Inc, Charleston, SC (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 30/10 (2020.01); G06F 111/20 (2020.01);
U.S. Cl.
CPC ...
G06F 30/10 (2020.01); G06F 2111/20 (2020.01);
Abstract

A digital documentation system for preparation of engineering documents utilizing one or more artificial intelligence (AI) algorithms is provided. The system includes a user interface for selecting and populating templates with data, and one or more AI algorithms for creating and recommending templates, and preparing documents based on the recommended templates. The system uses natural language processing and semantic analysis algorithms to understand the content of the templates, documents, and associated engineering data, and to generate and recommend relevant templates to the user based on user prompts. The system also uses machine learning and predictive modeling and decision-tree algorithms to assist with the preparation of documents, by generating suggestions for data fields and values based on the user's previous inputs and the overall context of the document and available engineering data, including model data and metadata from digital models accessed in a zero-trust framework.


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