Omaha, Nebraska – March 2025 – Aulendur Labs, an innovative technology startup specializing in advanced AI and machine learning solutions for defense applications, proudly announces the award of a significant Phase I contract by the Defense Threat Reduction Agency (DTRA). This contract supports the development of the groundbreaking Multi-source Joint Observation Leveraging Nuclear-detection Unification and Response (MJOLNuR) system.
What National Security Needs Does MJOLNuR Address?
MJOLNuR by Aulendur Labs addresses critical gaps in the U.S. nuclear detection infrastructure. Traditional systems like USAEDS face limitations in data integration and agility, restricting their ability to leverage modern satellite data and machine learning for nuclear threat detection.
The Defense Threat Reduction Agency (DTRA), a vital component of U.S. national security, is responsible for detecting and analyzing nuclear threats to protect military personnel, civilian populations, and critical infrastructure. Traditional systems, such as the United States Atomic Energy Detection System (USAEDS), currently face limitations in agility and data integration, restricting their effectiveness in leveraging advanced Earth Observation (EO) satellite data and modern machine learning technologies.
How Does MJOLNuR Revolutionize Nuclear Plume Detection?
MJOLNuR by Aulendur Labs integrates multispectral and hyperspectral satellite data with advanced weather forecasting models like GraphCast to create a dynamic digital twin of nuclear plumes — tracking composition, height, extent, and movement in real time immediately following a nuclear event.
Aulendur Labs' MJOLNuR system addresses these critical gaps through innovative integration of multispectral and hyperspectral satellite data, sophisticated data assimilation techniques, and advanced weather forecasting models. Central to MJOLNuR is its dynamic digital twin, a real-time digital model of nuclear plumes that tracks composition, height, extent, and movement immediately following a nuclear event.
MJOLNuR leverages advanced forecasting models, such as Google DeepMind's GraphCast, to deliver highly accurate, real-time predictions of nuclear plume dispersion. Adhering strictly to interoperability standards—including:
- Joint Enterprise Data Interoperability (JEDI)
- National Information Exchange Model (NIEM)
- Joint Center for Satellite Data Assimilation (JCSDA)
MJOLNuR ensures smooth integration and efficient dissemination of critical data to defense and civilian stakeholders.
What Does MJOLNuR's Phase I Research Involve?
MJOLNuR's seven-month Phase I contract funds Aulendur Labs to conduct foundational research and feasibility analysis — evaluating satellite products, determining nuclear plume material detectability, and analyzing integration pathways for a robust operational nuclear detection system.
The initial Phase I contract spans seven months, dedicated to foundational research and feasibility analysis. Aulendur's team will evaluate various satellite products, determine the detectability of nuclear plume materials, and analyze the integration of these capabilities into a robust operational system.
Aulendur is scheduled to meet with DTRA staff soon to finalize contract details, with project activities set to begin in late spring or early summer. The MJOLNuR system promises enhanced situational awareness, faster decision-making, and significantly reduced response times in nuclear incidents.
What Are MJOLNuR's Key Technical Objectives?
Aulendur Labs' MJOLNuR Phase I focuses on six critical objectives: cataloging satellite and forecasting products, understanding plume material detectability, evaluating raw and processed satellite data, assessing dispersion models like GraphCast, and determining operational deployment pathways.
Our Phase I work focuses on six critical objectives:
- Survey Candidate Products: Establish an exhaustive catalog of satellite and forecasting products
- Plume Materials Detectability: Understand nuclear plume composition and remote sensing detection methods
- Assess Level 1 Products: Evaluate raw satellite data for plume characterization
- Assess Level 2+ Products: Analyze processed geophysical quantities for nuclear plume analysis
- Assess Forecasting Products: Evaluate models like GALWEM, WRF, HRES, and GraphCast for dispersion prediction
- Operational Application Feasibility: Determine integration pathways for real-world deployment
How Is Aulendur Labs Committed to National Security?
"We are honored by DTRA's selection of our MJOLNuR proposal," stated Jorden Gershenson, CTO and co-founder of Aulendur Labs. "MJOLNuR will deliver an unprecedented capability addressing an urgent national security requirement. Our extensive experience with nuclear plume detection and advanced data integration uniquely positions us to accomplish this vital mission."
What Expertise Does the Aulendur Labs Team Bring?
The Aulendur Labs team brings direct, hands-on experience in nuclear plume detection from U.S. Air Force service — including operationalizing beta-gamma detectors for AFTAC, analyzing North Korean nuclear detonations for the Joint Chiefs of Staff, and guiding WC-135 Constant Phoenix aircraft into nuclear plumes.
Our team brings mission-critical experience to this challenge. During my service in the United States Air Force, I was instrumental in operationalizing and conducting R&D for deploying nuclear beta-gamma detectors for the Air Force Technical Applications Center's (AFTAC) unique mobile nuclear plume analysis laboratory. I conducted critical analyses of the North Korean nuclear detonations in 2016 and 2017, providing essential data to the Joint Chiefs of Staff.
As an airborne Scientific Applications Specialist, I learned to guide the WC-135 Constant Phoenix aircraft into nuclear plumes at various altitudes and under diverse meteorological conditions, tracking and analyzing invisible plume materials in real-time. This hands-on experience with nuclear plume detection directly informs our MJOLNuR development approach.
What Are the Potential Commercial Applications?
Beyond defense, MJOLNuR's satellite data fusion and atmospheric modeling technology by Aulendur Labs holds significant promise for environmental monitoring, aviation safety, agricultural forecasting, and insurance risk assessment — extending the same cross-domain intelligence capabilities to commercial sectors.
While MJOLNuR is primarily designed for defense applications, its technology also holds significant promise for commercial sectors, including:
- Environmental monitoring and pollution tracking
- Aviation safety (volcanic ash, hazardous airspace)
- Agricultural forecasting and climate modeling
- Insurance risk assessment for environmental disasters
What Is the Future for MJOLNuR and Aulendur Labs?
Beyond the DTRA contract, MJOLNuR by Aulendur Labs holds significant potential for enhancing AFTAC and USAEDS capabilities. AFTAC operates over 3,600 sensors globally and requires advanced, scalable solutions like MJOLNuR to meet growing nuclear detection demands.
Beyond DTRA, MJOLNuR holds significant potential for enhancing the capabilities of the Air Force Technical Applications Center (AFTAC) and the United States Atomic Energy Detection System (USAEDS). AFTAC operates the largest sensor network in the U.S. Air Force, with over 3,600 sensors globally, and requires advanced, scalable solutions like MJOLNuR to meet growing operational demands.
We're committed to delivering a validated, interoperable system that enhances national security through innovative technological advancement.
About Aulendur Labs
Founded by veterans Jorden Gershenson and Aaron Parker, Aulendur Labs provides cutting-edge AI/ML solutions focused on national defense and security. Drawing on real-world expertise in nuclear plume detection and satellite data integration, Aulendur Labs is committed to enhancing national security through innovative technological advancements.
Contact: info@aulendur.com
Frequently Asked Questions
MJOLNuR (Multi-source Joint Observation Leveraging Nuclear-detection Unification and Response) is a nuclear plume detection system developed by Aulendur Labs under a DTRA SBIR Phase I contract. MJOLNuR uses multi-source satellite data fusion and real-time atmospheric modeling to detect and characterize nuclear events.
Aulendur Labs won a Phase I SBIR award from the Defense Threat Reduction Agency (DTRA) under the USAEDS (United States Atomic Energy Detection System) program. The DTRA SBIR contract funds Aulendur Labs to develop MJOLNuR, a system for real-time nuclear plume detection using satellite data fusion and atmospheric physics modeling.
MJOLNuR validates Aulendur Labs' satellite data fusion and atmospheric modeling capabilities, which are key building blocks for DeepLoom. The digital twin technology that MJOLNuR develops for nuclear plumes directly informs how DeepLoom will model any atmospheric phenomenon at planetary scale.