The Department of Defense, specifically the Army, is seeking proposals for the development of an AI-enabled predictive logistics software solution under the SBIR program, titled "Predict, Optimize, Recommend, and Track for Adaptive Logistics (PORTAL)." The objective is to create a tool that enhances logistics operations at the Brigade level and below, capable of real-time tracking, predictive analysis, and generating AI-driven Courses of Action (COAs) to optimize logistical flow in contested environments. This initiative is crucial for improving the Army's ability to manage logistics effectively amidst disruptions and adversarial actions, ensuring mission success. Interested parties can submit Direct to Phase II proposals with a funding amount of up to $2,000,000, with the application due by July 23, 2025. For more information, visit the official solicitation page at https://www.dodsbirsttr.mil/topics-app/.

## Description

Modern military operations require agile and resilient logistics in contested environments. Traditional logistics systems struggle to integrate data from disparate sources across Army platforms and the Army is interested in enhancing their capability to rapidly handle changing situations, disruptions, and adversarial actions. Data from logistics systems such as the Joint Battle Command Platform (JBC-P), Global Combat Support System-Army (GCSS-A), and SAP ERP (Enterprise Resource Planning) could be easier to understand and action if displayed in a more user-centric format. This topic should include AI technology to provide commanders with a comprehensive logistics awareness and decision-making tool that is easy to understand and accessible. The tool should have the ability to track, predict, and recommend, as defined below:<ol><li>Track: Provide a real-time view of logistics assets, personnel, and supply chains. Create a Common Operating Picture (COP), which clearly depicts inventory (commodities, fuel, ammunition, etc.), vehicle status, and capabilities, while synchronizing efforts and providing commanders with accurate information. This topic will go beyond traditional analog tracking measures to increase awareness and provide real time inventory, status, and resupply requirements for operational units.</li><li>Predict: Anticipate potential disruptions, like bottlenecks and logistical shortfalls, using predictive modeling. Forecast individual unit consumption, by classes of supply, to identify problems before they become emergencies. Automatically identify and alert (with advanced notice) when planned resupply operations are insufficient, which can lead to critical shortages.</li><li>Recommend: Generate optimized COAs for routes, resupply packages, resource allocation, and risk mitigation. Automatically plan resupply routes and packages to optimize equipment and personnel utilization.</li></ol>Solutions to be considered will include, but are not limited to, the following capabilities: <ol><li>Operate in denied, disrupted, intermittent, and limited (DDIL) environments with low bandwidths (&lt;10Mbps).</li><li>Ingest data from the Joint Battle Command Platform (JBCP), Global Combat Support System-Army (GCSS-A), and other inventory management system(s) such as SAP ERP. Awardees will have access to historical data, in the form of electronic spreadsheets, for training purposes. More details will be made available to the awardee(s). It is expected that the final software and developed algorithms will reside on laptops used for logistics purposes and should be fully operable with limited or no internet connection. Full integration with JBCP andGCSS-A is a future endeavor but should be considered during development.</li><li>Modular Open Systems Approach (MOSA) compliant (see reference 3).</li></ol>PORTAL Webinar:<ul><li>Date: Tuesday, June 10 at 11:00AM CST</li><li>Registration Link: https://us06web.zoom.us/webinar/register/WN_3TnciAUFTsKJonR54Dr0zw</li></ul>

## Objective

Develop an AI-enabled predictive logistics software solution, to be used at the Brigade level and below, capable of operating in contested environments, providing real-time tracking, predictive analysis, and AI-generated Courses of Action (COAs) to optimize logistical flow and facilitate mission success.

## Phase I

This topic is accepting Direct to Phase II proposals for a cost up to $2,000,000 for an 18-month period of performance.Proposers interested in submitting a DP2 proposal must provide documentation to substantiate that the scientific and technical merit and feasibility equivalent to a Phase I project has been met. Documentation can include data, reports, specific measurements, success criteria of a prototype, etc.

## Phase II

The concept of predictive logistics tracking software has been realized in the commercial sector by multiple companies. Companies have achieved TRL 5-6. Companies have taken different approaches to creating AI-enabled logistical software, with widespread success. The DP2 SBIR will facilitate rigorous testing for selected companies and provide end user feedback for iterative improvement. Refine the preliminary design proposed in the solicitation and create a prototype PORTAL software platform. Companies should work toward connecting this tool to existing military logistics systems and data sources. The final product should improve data flow while receiving and sending data into programs of record (Global Combat Support System-Army) with the aim of working to achieve an Interim Authorization to Test (IATT) and full Authority to Operate (ATO). These goals should be accomplished through training and refining developed models using real-world data and feedback from logistics personnel by leveraging the Southern Border Mission. The software should generate nuanced and contextually relevant COAs, including alternative options and risk assessments. Execute deliberate after-action reviews (AARs) after training events to iteratively evaluate recommended COAs. Create an intuitive and user-friendly interface for visualizing logistics information and interacting with AI-generated recommendations. Phase II testing should analyze platform capabilities under denied, degraded, intermittent, and latent (DDIL) conditions. Companies should budget for quarterly travel to the supported unit conducting rigorous testing and receiving unit feedback (6 visits total over the 18-month period of performance).

## Phase III: Dual Use Applications

Commercial applications for logistical optimization and AI integration include but are not limited to humanitarian aid and disaster relief, supply chain management, delivery scheduling, and traffic management. The ability to analyze current logistical operations, optimize efficiency, and receive AI powered recommendations represents a key capability for commercial application.<ul><li>Humanitarian Aid and Disaster Relief: Optimize logistics flows in challenging environments during natural disasters or humanitarian crises.</li><li>Supply Chain Management: Enhance commercial supply chain visibility, resilience, and efficiency.</li><li>Delivery Scheduling: AI-planned routes to optimize speed and fuel efficiency for shortest routes.</li><li>Traffic Management: Improve real-time traffic flow and optimize transportation routes in congested urban environments.</li></ul>

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Predict, Optimize, Recommend, and Track for Adaptive Logistics (PORTAL)​

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Predict, Optimize, Recommend, and Track for Adaptive Logistics (PORTAL)