Istari Digital, Inc.

Istari, Inc.

Christopher Benson

William Roper, Jr

Sriram Krishnan

Long N Phan

Alethea Duhon

Peter Galvin

Baha Aldeen E A Abunojaim

Baha Abu Nojaim

Ellie Marie Daw

Danne Stayskal Huffaker

Omar Valverde

James C Pavur

Pranav Sumanth Doijode

Najem Aldeen Abu Rmaileh

Christopher Alexis Kotelly

Paul A DeBitetto

Thomas A Campbell

Sanjay Emani Sarma

Brendan Lee

Abdullah M S Al-Hatem

Hillary Hester

Kyle Caldwell

Abraham Aldaraca

Michael Welles

Eric Watz

Joshua Adam Marks

Bayan Abedal-Muttaleb Afif Hashem

Mohammad M Y Zahra

Ross Billings

Mohammad Zahra

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.

Artificial intelligence (AI) assisted digital documentation for digital engineering

Methods and systems for a document review process are provided. The method includes receiving an input digital model representation comprising at least one externally-accessible model endpoint for generating a digital artifact. Then, generating a document splice comprising access to multiple document subunits, with at least one document subunit written in a natural language and comprising the digital artifact; the access to each document subunit is provided through an externally-accessible document endpoint for the subunit. Then, generating a document by combining the document subunits, and generating a view associated with the document, based on an user authorization result including selective access rights to the document subunits. The view comprises access to the digital model representation, the digital artifact, each document subunit, and the document. Finally, receiving a user input and updating, via one of the externally-accessible document endpoints, the document splice based on the user input.

Multimodal digital document interfaces for dynamic and collaborative reviews

Methods and systems for generating digital threads that connect models and software tools for an interconnected digital engineering and certification ecosystem are provided. In one embodiment, a process for generating a software-code-defined digital thread includes receiving a first model representation of a first engineering model, a second model representation of a second engineering model, and an intent input. Determining, using a machine learning (ML) model, one or more model endpoints in the first and the second model representations. Generating, using a script-generating ML model, a platform orchestration script that accomplishes the intent input by connecting the first model representation and the second model representation, using the one or more model endpoints. Finally, storing the platform orchestration script as the software-code-defined digital thread. The digital threading of digital engineering models, with and without AI assistance, leads to exponential increases in efficiency of designing, testing, certifying, manufacturing, and operating physical products, allowing physical products to be made at digital speeds.

Software-code-defined digital threads in digital engineering systems with artificial intelligence (AI) assistance

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for quantifying avoided carbon emissions. The approach includes receiving, from a client device in communication with a digital platform, a request to execute a task by the digital platform. A token is assigned by the digital platform, the token is configured to uniquely identify the received request to execute the task using the digital platform. The digital platform receives a first value representing a baseline execution cost associated with executing the task. The digital platform determines, using the assigned token and based on execution of the task using the digital platform, a second value representing a reduction in execution cost attained by using the digital platform. The digital platform generates, based on a comparison of the second value to the first value, an attained execution reduction cost associated with the execution of the task by the digital platform.

Architecture for quantifying avoided carbon emissions in a digital engineering platform

Methods and systems for generating a sharable script related to an input digital model on a digital platform are provided. The method includes receiving a user request indicative of a digital task involving an input digital model, and retrieving a corresponding input digital model file. Then, determining characteristic attributes of the input digital model, where the characteristic attributes include digital artifacts generated from the input digital model file. Then, selecting from a collection of templates, using a machine learning (ML) engine, a template matching the characteristic attributes of the input digital model. The ML engine may be trained on documentations of digital tools integrated into the digital platform, a resource-capability mapping of the digital platform, and sample digital thread orchestration scripts collected through past uses of the digital platform. Finally, the method includes generating the sharable script that implements the digital task, based on the selected template.

Machine learning engine for workflow enhancement in digital workflows

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for security of a digital engineering ecosystem. In some implementations, a digital platform receives a request to execute an operation on a digital model. The digital platform generates a fungible idempotent token that uniquely identifies the request. The digital platform selects data that identifies one or more tools for executing the operation. The digital platform generates one or more nonfungible idempotent tokens associated with the data that identifies the one or more selected tools. The digital platform executes the operation on the digital model using the tools. While executing the operation, the digital platform determines whether to additionally execute the operation on the digital model based on a subsequent request. In response to determining that the additional execution of the operation has been requested while the operation is being executed, the digital platform prevents the additional execution.

Token management in a digital engineering platform

An unmanned vehicle includes at least one navigation sensor configured to measure navigation data indicative of an environment, at least one status sensor configured to measure status data indicative of operating parameters of a hardware system and a computing system. The computing system includes a navigation engine configured to receive the navigation data and status data and plan a path through the environment and a security engine. The security engine is configured to detect that an unauthorized user is attempting to access the navigation data or the status data, send an alert to an authorized user indicating that the unauthorized user is attempting to access navigation data or status data, and send, to the unauthorized user, simulated data including one or both of simulated navigation data and simulated status data.

Security system for an unmanned vehicle

Methods and systems for generating a sharable model splice of a digital engineering (DE) model are provided. The method comprises receiving a DE model file in a native file format; extracting model data; storing the model data in a storage area; generating external, commonly-accessible splice functions that enable external access to digital artifacts derived from the model data; and generating the sharable model splice, which comprises access to a selective portion of the digital artifacts, and access to at least one of the splice functions. The splice functions provide addressable API or SDK endpoints that enable access by third-party applications and users to the digital artifacts without access to an entirety of the DE model file and without requiring direct engagement with a DE tool associated with the DE model type. These endpoints also provide a unified programming interface to sharable model splices generated from DE models.

Secure and scalable model splicing of digital engineering models for software-code-defined digital threads

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for secure communications in a digital engineering ecosystem. In some implementations, a digital platform receives a request from a user device to interact with a digital model. The digital platform determines whether a user operating the user device is authorized. In response to determining the user is authorized to access the digital platform, the digital platform generates a token that provides the user with access to the digital platform. The digital platform determines whether the request includes malicious activity. In response to determining that the request is absent of the malicious activity, the digital platform executes a digital thread that executes one or more operations using digital tools and the digital model. The digital platform provides data indicative of the one or more operations executing the digital thread to the user device.

Securing an interconnected digital engineering and certification ecosystem

A computer-implemented method includes receiving design and/or engineering data (D/E data) corresponding to a prototype representation of a product and transmitting one or more inputs derived from the D/E data to one or more digital engineering tools for processing. The method also includes receiving engineering-related data outputs from the one or more digital engineering tools and receiving data corresponding to one or more common validation and verification (V&V products). The method further includes identifying one or more requirements for the product based on the data corresponding to the one or more common V&V products; determining whether or not the one or more requirements have been satisfied; and presenting information corresponding to the engineering-related data outputs and/or the data corresponding to the one or more common V&V products. The method also includes receiving instructions from the user device, and performing one or more manipulations of the D/E data.

Interconnected digital engineering and certification ecosystem

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for securely certifying products in an ecosystem. In some implementations, a digital platform receives a user request to access digital models. The digital platform determines whether the user is authorized to access the digital models. In response, the digital platform generates a transaction request to send to a location of the digital models, wherein the transaction request comprises data identifying operations to perform using the digital models. The digital platform transmits, to the location of the digital models, the generated transaction request that causes execution of the operations. The digital platform receives data representative of a result of the operations performed. The digital platform provides, to a user interface of the user device, the data representative of the result. The digital platform audits the data related to the transaction request and the data representative of the result.

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Charleston, SC, United States of America

Christopher Benson