

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.
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:
Solutions to be considered will include, but are not limited to, the following capabilities:
PORTAL Webinar:
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.
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).
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.
For more information, and to submit your full proposal package, visit the DSIP Portal.
View the SBIR Component Instructions.
SBIR|STTR Help Desk: usarmy.sbirsttr@army.mil
References:
KEYWORDS: Contested Logistics; AI-Enabled Logistics; Predictive Analytics; Course of Action Generation; Military Logistics; Software; Decision Support
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.
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:
Solutions to be considered will include, but are not limited to, the following capabilities:
PORTAL Webinar:
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.
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).
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.
For more information, and to submit your full proposal package, visit the DSIP Portal.
View the SBIR Component Instructions.
SBIR|STTR Help Desk: usarmy.sbirsttr@army.mil
References:
KEYWORDS: Contested Logistics; AI-Enabled Logistics; Predictive Analytics; Course of Action Generation; Military Logistics; Software; Decision Support