SBIR/STTR Research Award

System for Efficient Authoring and Smart Condition Reporting and Intelligent Baseline Evaluation (SEASCRIBE)

Award identifier 23681c6a80b2d3024f383168e1a517e9ca4a1256d9f9a349761f9bc7a4a13695Awarding agency Department of Defense · Navy

Award amount

$240,000

Program and phase

SBIR · Phase I

Award year

2024

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
KNOWLEDGE BASED SYSTEMS INC
Proposal award date
2024-07-15
Contract end date
2025-09-06
UEI
YJXQFQ83DQR4
Solicitation number
24.1
Topic code
N241-055

Research abstract

The Maintenance Data System (MDS) provides useful capabilities for enhanced Naval operational efficiency, serving as a platform for maintenance personnel to report corrective actions across equipment categories. Forms such as the OPNAV 4790 and the 2-kilo are integral to the Navy's strategic maintenance framework. Once submitted, the information contained in these forms becomes accessible by a several different authorized users, including the Type Commander (TYCOM) and the Navy Maintenance Support Office Department within the Naval Sea Logistics Center. The information managed through the proper use of these forms play a crucial role in analyzing maintenance challenges, developing current ship maintenance projects (CSMP), and generating automated work requests for deferred maintenance actions. However, the utility of the MDS is compromised when the forms are filled incompletely or inaccurately. Errors impact immediate maintenance needs, operational readiness, and long-term strategic planning. Addressing these challenges requires innovative concepts such as the idea of 'curation while creation' using AI-assisted technologies to enhance the reliability and accuracy of essential documents in naval operations. Leveraging generative AI represents a significant leap forward, to enable intelligent parsing and integration of technical data, maintenance logs, and operational manuals for accurate form completion. Through the use of natural language processing and machine learning methods, generative AI ensures consistency, reduces human error, and speeds up the documentation process. Recognizing these challenges and opportunities, Knowledge Based Systems, Inc. (KBSI) will research and demonstrate the System for Efficient Authoring and Smart Condition Reporting and Intelligent Baseline Evaluation (SEASCRIBE). By harnessing natural language processing and generative AI, the proposed solution will ensure consistency, reduce human error, and significantly speed up the documentation process. SEASCRIBE will have the ability to learn and adapt to domain-specific vocabularies and the unique requirements of naval maintenance. The resulting new capability will help streamline naval maintenance tasks while enhancing the overall efficiency and reliability of maintenance management in naval operations.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

263 SBIR/STTR records share this UEI (1989–2025). Reported award amounts total $101,235,617. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Commerce, National Science Foundation, Department of Transportation, Department of Energy

Agency intelligence

Department of Defense

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