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SI/ML Model Development and Optimization

Open
SBIR / STTR

Contract Overview

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This subcontract for the United States Navy focuses on the research and design of Super Intelligence and Machine Learning methods to support prime contractors on STTR projects. The primary objective is to develop models that map parameter count to performance while creating explainable logic pathways and reliability metrics to remove black box vulnerabilities. Additionally, the project requires the optimization of these models for deployment on low-cost CPU and embedded edge hardware, culminating in the delivery of a prototype methodology and a technical feasibility report. The opportunity is a total small business set-aside under NAICS code 541511, specifically mandated for firms with fewer than 500 employees. Due to the nature of the defense work, contractors must maintain CMMC Level 2 compliance. Interested parties must respond by December 2, 2026, to participate in this Department of Defense initiative.

General Info

Navy subcontract for explainable AI/ML research and edge hardware optimization for small businesses.

Documents

This scope was carved out of DON27TZ02-NV002.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

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Field-Friendly Artificial Intelligence and Machine Learning Systems

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Organization & Contact Information

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AgencyDepartment of Defense → United States Navy
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Performs research and design of a Super Intelligence/Machine Learning (SI/ML) method for prime contractors on US Navy STTR projects. Develops models mapping parameter count to performance, designs explainable logic pathways, and implements reliability metrics to eliminate black box vulnerabilities. Optimizes models for low-cost CPU and embedded edge hardware. Requires CMMC Level 2 compliance. Delivers a technical feasibility report and a prototype methodology.

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