SBIR/STTR Research Award

CAMBER: Copilot Analytics for Maintenance and Better Efficiency in Reporting - Mission-focused Generative AI & LLM Applications

Award identifier d783411afd4bdadd7913202f6cbfdede8a98f9516e3fbadca89d86a97d9f8beaAwarding agency Department of Defense · Air Force

Award amount

$1,249,992

Program and phase

SBIR · Phase II

Award year

2024

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
COLVIN RUN NETWORKS, INC
Proposal award date
2024-02-06
Contract end date
2025-11-12
UEI
Z475KM9G68V8
Solicitation number
X23.5
Topic code
AFX235-CSO1

Research abstract

CAMBER: Enhancing USAF Maintenance Efficiency with AI-Driven Analytics The CAMBER proposal presents a transformative approach to address the United States Air Force's (USAF) critical need for improved maintenance efficiency and operational readiness. Leveraging the success of a Phase I Generative AI proof-of-concept, this proposal outlines the development and integration of a Large Language Model (LLM)-based system designed to streamline data processing and intelligence reporting. At the core of CAMBER lies an AI solution that enables rapid sifting through vast datasets to produce actionable insights, thereby amplifying mission effectiveness and maintainer proficiency. This system addresses the “garbage in, garbage out” challenge by refining data inputs into quality outputs, providing a higher level of analysis than is currently achievable by human efforts alone. The proposed Phase II initiative follows a structured RDT&E approach to ensure the AI system aligns with USAF operational needs and the mental models of maintainers. It encompasses requirement analysis, data collection, model selection, prototype development, and iterative testing. The project will culminate in operational integration and evaluation, with a continuous feedback loop post-deployment for performance optimization. CAMBER promises to be a pioneering step in the digital transformation of USAF maintenance operations. By integrating into legacy systems and operational workflows, it will serve as an AI-driven analytic co-pilot, enhancing decision-making and efficiency. The anticipated outcomes include significant reductions in time spent on maintenance tasks and a corresponding increase in operational preparedness. The proposal demonstrates a strong potential for commercialization, backed by industry partnerships and commitments from defense stakeholders. CAMBER's non-defense commercial applications are also outlined, highlighting its capability to process and analyze large volumes of structured and unstructured data to support various industries reliant on heavy machinery and equipment. In line with Air Force priorities and the broader Department of Defense objectives, CAMBER represents a significant advancement in operational capabilities. It stands to redefine maintenance and operational reporting, supporting the USAF's pursuit of innovation and excellence, and ensuring that the Air Force remains at the forefront of technological advancements in strategic national defense.

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

29 SBIR/STTR records share this UEI (2019–2025). Reported award amounts total $17,976,875. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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