NPS graduate builds AI logistics tool for 2nd Marine Logistics Group

U.S. Marine Corps Maj. Nickolas Mohr is applying his Naval Postgraduate School computer science training to help 2nd Marine Logistics Group assess readiness and capacity with a new AI-enabled logistics tool. The effort could give commanders faster, data-driven answers on whether they can support a deployment or training event. Why it matters: - Maj. Nickolas Mohr’s work aims to turn logistics planning from a manual, spreadsheet-heavy process into a real-time decision tool for Marine Corps commanders. - The Logistics Capacity Estimator could help 2nd Marine Logistics Group spot gaps in personnel, equipment and readiness before a unit reaches its limits. - Faster, better-informed capacity checks can affect deployments, training schedules and how the unit manages strain on Marines. What happened: - Mohr, a U.S. Marine Corps major and Naval Postgraduate School alumnus, graduated from NPS in September 2025 with a master’s degree in computer science. - He checked into 2nd Marine Logistics Group in November 2025 and began applying AI and data analytics to operational problems. - Mohr is building the Logistics Capacity Estimator, a visualization tool that uses real-time unit data to help commanders understand whether a unit can support a mission. - U.S. Marine Corps Col. Daniel Coleman, chief of staff for 2nd Marine Logistics Group, said data and artificial intelligence are an operational imperative and said Mohr applies his NPS training daily in the unit’s Command Data Analytics and Artificial Intelligence Office. The details: - The Logistics Capacity Estimator uses the Palantir Maven Smart System platform. - The tool pulls real-time data from authoritative Marine Corps and Navy systems. - Planners can define an event, such as a deployment or training exercise, and specify required Marines, ranks, Military Occupational Specialties and equipment. - The system overlays those requirements on current unit strength to show gaps and areas needing support. - The process replaces a manual workflow that often depends on outdated data and subjective judgment. - Mohr said the system is designed to answer two questions quickly: whether a unit can support a mission right now and, if not, why not. - The tool also aims to capture human readiness factors, including Marines who may be nominally available but under heavy stress from back-to-back deployments. - Mohr hopes to extend the system with historical personnel data and predictive analytics to forecast manpower shortfalls and operational tempo. - He said future versions could analyze five years of historical data on who is coming in and who is leaving to predict where gaps will occur. Between the lines: - Mohr’s NPS thesis, “Red Team Log Analysis: Tools for Enhancing Cyber Security Operations and Analysis,” gave him experience with machine learning, cyberattack logs and problem framing. - Alan Shaffer, a computer science professor and Mohr’s thesis advisor, said Mohr expanded the project beyond its original scope when real-world data was limited. - Shaffer said Mohr experimented with large language models to generate realistic log data for machine learning training. - The logistics project shows how research skills from NPS can move directly into unit-level operations. - The effort also reflects a broader push inside the Marine Corps to use data and AI for faster operational decisions rather than relying mainly on institutional memory and manual analysis. What’s next: - Mohr and his team will keep developing the Logistics Capacity Estimator as they refine data inputs and improve how commanders see readiness limits. - Future work will focus on predictive analytics built on historical personnel trends. - The Marine Corps could use the model as a template for other units that need a clearer view of capacity and sustainment. The bottom line: - Mohr’s transition from NPS student to operational AI developer shows how specialized graduate education is being turned into practical tools for Marine Corps logistics and readiness.**