SBIR/STTR Research Award

RADIANT: Radiation AI Decision and Information Assistant for Nuclear Tasks

Award identifier c1be265b345fcca7ae8ff70ef410cf0dcc9a3027ce557d5985b2ba30f47a773aAwarding agency Department of Defense · Defense Threat Reduction Agency

Award amount

$199,984

Program and phase

STTR · Phase I

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Defense Threat Reduction Agency
Recipient company
REDSHRED, LLC
Proposal award date
2025-08-01
Contract end date
2026-03-03
UEI
GU8RZGZXU5K7
Solicitation number
24.C
Topic code
DTRA24C-002

Research abstract

The Defense Threat Reduction Agency (DTRA) faces a critical challenge in developing an AI radiation health physicist companion to enhance radiation safety during military operations. The current state of radiation exposure management lacks real-time, user-friendly guidance that can be efficiently delivered on small local machines. This gap poses significant risks to personnel operating in environments with potential radiation hazards, as existing solutions do not adequately translate complex radiation data into actionable insights for non-experts. The significance of addressing this problem lies in the potential to revolutionize radiation safety protocols. Current methods often require specialized knowledge and are not accessible to all military personnel, which can lead to delayed decision-making and increased exposure risks. The ability to provide immediate, comprehensible advice on radiation exposure is crucial for maintaining operational effectiveness and safeguarding health. Ensuring that personnel can quickly assess and respond to radiation threats supports the resilience of all personnel and enhances overall readiness, reducing the risk of operational degradation due to radiation. Furthermore, the need for accurate and timely radiation exposure information is not being satisfactorily met by current technologies. Existing systems often lack the capability to integrate real-time dosimetry measurements with predictive analytics, which is essential for assessing the impact of radiation on combat power and mission success. To address this need, Redshred proposes to develop the Radiation AI Decision and Information Assistant for Nuclear Tasks (RADIANT), based on advanced machine learning and AI methodologies. Specifically, the innovation in leveraging Redshred’s TRACEE technology will improve performance in areas such as real-time data extraction, translation, and code generation. This technology will meet specifications by efficiently interpreting radiation data and providing user-friendly guidance. As a result, RADIANT offers enhanced decision-making capabilities and risk management in radiation exposure scenarios.

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

21 SBIR/STTR records share this UEI (2016–2026). Reported award amounts total $15,835,083. Reported amounts are not federal obligations.

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

Agencies: Department of Defense, National Science Foundation, Department of Commerce

Agency intelligence

Department of Defense

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