Above: Cargo pallets are removed from a C-17 Globemaster III in Port-Au-Prince, Haiti. The C-17 delivered soldiers, a truck with water tank, and pallets of gear to be used in the Haiti relief effort. (U.S. Air Force photo/Senior Airman Laura Turner) The appearance of U.S. Department of Defense (DoD) visual information does not imply or constitute DoD endorsement.

Tapestry Solutions, a Boeing company, is applying artificial intelligence (AI) and machine learning (ML) to its software solution to improve the speed and accuracy of aircraft- and ship-load planning for the U.S. Department of Defense.

Why it matters: Increasingly, contested logistics environments faced by the Defense Transportation System have led the U.S. Surface Deployment and Distribution Command to prioritize data-driven decision-making, embedded analytics, and AI/ML capabilities to increase agility and responsiveness.

Above: ICODES Single Load Planner application. (© Boeing)

How it works: Key features of the Transportation Intelligence Environment (TIE) include:

• Historical records: Previously executed plans are organized into a historical data repository for use by ML services.
• Transportation documentation: Extensive Integrated Computerized Deployment System (ICODES) documentation is processed into a vector database for use by generative AI services.
• AI/ML services: Nine experimental AI/ML capabilities are implemented within reusable web services with application programming interfaces for building end-user application features.
• Application prototypes: Prototype AI/ML tools include a Cargo Assistant to help enter and validate cargo data, a Free Query application with interactive map for custom reports and data analytics, and a Help Chat agent that answers user questions and assists with training.

What they're saying: “TIE represents a major step forward in how we support military transportation planning,” said Debbie Churchill, Tapestry president and CEO. “By harnessing AI and machine learning, we’re helping the Defense Transportation System become faster, smarter and more agile in meeting today’s complex challenges.”

What’s next: Demonstrations of the TIE application prototypes have garnered strong customer interest, securing funding for production system capabilities that will further automate load-planning operations and improve transportation data quality.

• The government has selected eight of the nine experimental AI/ML capabilities for full development, with production deployment targeted for June 2026.