Armada Collaborates with Carnegie Mellon University’s Heinz College of Information Systems and Public Policy on AI-Driven Capstone Projects

Three student-led capstone projects focused on improving food safety compliance, inventory optimization, and delivery accuracy

PITTSBURGH, Aug. 24, 2026 (GLOBE NEWSWIRE) -- Armada, a leading provider of supply chain solutions, today announced the successful completion of three artificial intelligence–focused capstone projects in collaboration with Carnegie Mellon University’s Heinz College of Information Systems and Public Policy.

The projects reflect Armada’s continued investment in AI and advanced analytics to improve operational performance, strengthen regulatory compliance, and enhance supply chain resiliency. By working with graduate students on clearly defined business challenges, Armada accelerated the development of scalable solutions with measurable operational impact.

The three Capstone projects included initiatives focused on applying AI and advanced analytics to key supply chain challenges:

Food Safety Automation and Traceability

The team developed a hybrid AI system to automate the classification of regulated products under evolving food safety requirements, including FDA FSMA 204, USDA rules, and California Proposition 12. The solution combines rule-based logic, semantic embeddings, and large language model reasoning to deliver 90% automated classification accuracy for items requiring advanced review. The system reduces manual analysis by 70–85%, decreases processing time from days to minutes, and produces audit-ready, explainable outputs to support regulatory compliance and traceability.

Safety Stock Optimization

This project applied AI-driven modeling to optimize safety stock levels across restaurant supply chains. The solution helps ensure product availability while minimizing excess inventory and food waste. By balancing service levels with efficiency, Armada can improve operational performance and support more sustainable inventory management practices.

ETA Accuracy Improvement

To address costly ETA inaccuracies, the student team built a machine learning model using cleaned shipment and GPS data. Leveraging gradient-boosted decision trees, the model reduced mean absolute error by 53%, an average improvement of 124 minutes, across 1.76 million predictions.

“These projects reflect how Armada is thoughtfully embedding AI into the core of our business,” said Chris O’Brien, CEO of Armada. “From strengthening regulatory compliance to enhancing predictive logistics to deploying AI agents for autonomous operations, we are applying AI and advanced analytics to tackle complex supply chain challenges in ways that are practical, measurable, and built to scale.”

This collaboration provided Heinz College students with hands-on experience addressing complex logistics and regulatory challenges, while enabling Armada to further embed AI-driven decision-making across its organization. Katherine Karolick, CIO at Armada, added, “Collaborations like this allow us to move faster, think bigger, and continue delivering smarter solutions for our customers. Carnegie Mellon is a world leader in AI, and working together is one more way we stay at the forefront of advanced thinking in this area.”

Armada continues to expand its focus on innovation and AI as it broadens its capabilities across the supply chain landscape. To learn more about Armada’s AI-driven supply chain solutions, visit www.armada.net.

About Armada Supply Chain Solutions

Armada delivers innovative, data-driven supply chain solutions that enhance performance, reduce risk, and drive sustainable results. From freight management to inventory optimization, network analytics, and real-time visibility, our integrated services are built to power future-ready supply chains. Learn more at www.armada.net.

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