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LSUBP00004 Information Warfare Research Project 3 (IWRP-3), Project Number 26-LANT-2974 MBSE with AI Plug-In Prototype (C)

Active
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The Naval Information Warfare Systems Atlantic is seeking to advance its Model-Based Systems Engineering (MBSE) capabilities by integrating Generative AI, specifically GPT-based technologies, into its Cameo Systems Modeler environment to enhance the development, validation, and documentation of SysML and UAF models. The goal is to develop a robust plugin that automates key MBSE tasks such as requirements generation and analysis, creation and validation of SysML elements, generation of UAF viewpoints including Strategic, Operational, and System views, and the direct production of structured documentation—all within the Cameo platform. The contractor must demonstrate proven experience building AI-driven plugins for Cameo SysML in defense or government contexts, with a strong focus on domain-specific fine-tuning of large language models using MIL-STD requirements, Department of Defense architecture standards, and UAF metamodels to ensure high accuracy and relevance in military system development. Proposals must address full integration compatibility with current and future versions of Cameo Systems Modeler, adherence to government data security and compliance standards, and the delivery of comprehensive training and enablement programs for NIWC engineering teams. The solution must include clear strategies for ongoing maintenance, support, and continuous improvement, with emphasis on safeguarding sensitive data throughout the development lifecycle. The project, identified under IWRP-3 with project number 26-LANT-2974, seeks to reduce time-to-market, lower development costs, and significantly improve the quality, security, and reliability of defense systems by embedding AI-powered automation directly into NIWC’s MBSE workflow. Interested vendors should respond to the point of contact, Anthony Berkos, with detailed capabilities demonstrating alignment with these technical and operational objectives.

General Info

Integrate GPT-based AI into Cameo SysML to automate MBSE tasks per DoD standards with secure, compliant, trained solutions.

Agency

Naval Information Warfare Systems → Niwc AtlanticView Agency

NAICS

N/A

Place of Performance

Charleston, SC, US

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

Posted

forecast

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Organization & Contact Information

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AgencyNaval Information Warfare Systems → Niwc Atlantic
Contacts2 people available
OfficeN/A
Organization / Agency
Naval Information Warfare Systems → Niwc Atlantic
View Agency Profile
Office AddressN/A
Contacts
Berkos Anthony AContracting Officer
Kristopher GarrisSecondary Point of Contact

Full Description

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NIWC is exploring the potential of integrating Generative AI, specifically GPT technology, into our Cameo Systems Modeler (SysML) workflows to optimize efficiency, improve data integrity, and enhance collaboration across project teams. We are seeking information from qualified vendors capable of providing a robust and integrated Cameo SysML plugin that leverages GPT for tasks such as requirements analysis and generation, automated model element creation and validation (including the generation of UAF viewpoints and SysML diagrams), and streamlined documentation generation directly within the Cameo environment. We aim to identify partners who can demonstrate a proven track record of success in developing and deploying AI-driven Cameo SysML plugins that specifically support both SysML and UAF modeling, ideally within the defense or government contracting sector.
This Request for Information (RFI) is intended to gather insights into potential Cameo SysML plugin solutions that can seamlessly integrate with our existing MBSE toolchain and data architecture, with a particular focus on generating and managing UAF models. We are particularly interested in understanding how vendors can fine-tune LLMs with domain-specific knowledge (e.g., MIL-STD requirements, DoD architectures, UAF metamodel) to ensure optimal performance and accuracy in both SysML and UAF contexts. Furthermore, we seek clarity on plugin architecture and compatibility with various Cameo versions, the ability to generate and manage UAF viewpoints (e.g., Strategic, Operational, System), training and enablement programs for NIWC engineers focused on both SysML and UAF with AI assistance, ongoing support and maintenance strategies, and approaches to ensuring data security and compliance with relevant government regulations . Ultimately, our goal is to identify a partner who can enable us to achieve significant improvements in our system development lifecycle, reducing time-to-market, optimizing costs, and increasing the overall quality, security, and reliability of our systems developed using Cameo Systems Modeler, with seamless support for both SysML and UAF modeling paradigms.

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