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AI Solutions for Real-World Supply Chain Challenges

The Center for Supply Chain Excellence helps organizations enable, implement, and sustain AI applications that solve practical supply chain problems.

The Saint Louis University Center for Supply Chain Excellence partners with organizations to identify high-value supply chain challenges and develop applied AI solutions that improve speed, visibility, accuracy and decision-making. The goal is not simply to showcase technology, but to help companies move from concept to execution by designing practical tools that can be implemented, adopted, and maintained over time.

What Makes Our Approach Different

The SLU center’s strength is its ability to connect supply chain expertise with applied AI problem solving. Projects are grounded in real operational needs and designed to support implementation in business settings where data quality, process variation, and user adoption matter as much as the technology itself.

The center can support organizations across the full lifecycle of AI in supply chain:

  • Identifying and prioritizing high-value use cases
  • Translating operational pain points into practical AI applications
  • Building solutions that combine automation with human review
  • Supporting implementation, testing, and workflow integration
  • Improving long-term adoption through refinement and continuous learning

Areas of Strength in AI and Supply Chain

The center’s project capabilities can support a range of use cases across supply chain operations, including:

  • Document intelligence and data extraction
  • Demand and inventory decision support
  • Procurement and sourcing analytics
  • Workflow automation for supply chain operations
  • AI-assisted exception handling and review
  • Decision dashboards and process visibility
  • Human-in-the-loop AI systems for operational accuracy

Featured Project

AI-Powered FF&E Extraction for Hotel Renovation Supply Chains

This project demonstrates how AI can solve a time-consuming and detail-heavy supply chain problem. Hotel renovation teams often need to determine exactly what furniture, fixtures and equipment must be ordered for a renovation project based on large architectural drawing packages. Traditionally, this process requires teams to manually review floor plans, specifications and elevation drawings page by page, then build order quantities by room type in spreadsheets.

The application streamlines that workflow by using AI to read architectural package PDFs and extract structured procurement information. Users upload the architectural package, and the system identifies the hotel name, room types, and the pages where relevant information appears. Users can review and correct these initial interpretations before the system continues.

The AI then analyzes each relevant page to identify furniture, fixtures, and equipment items such as beds, desks, lamps, curtains, shower curtains, and seating, along with the quantity required for each room type. The system multiplies these quantities by the number of rooms, flags lower-confidence results for review, and gives the user an opportunity to edit, approve, or remove items before finalization.

Once approved, the application exports a structured bid spreadsheet that is ready to share with vendors for pricing. The solution also improves over time by learning from user corrections, and it includes workflow support features such as Google Drive backup and a dashboard that tracks AI processing activity and cost.

In practical terms, the application transforms a stack of architectural PDFs into a clean, organized order list for FF&E procurement. A process that once took days of manual effort can now be completed with much greater speed, consistency and visibility.

Why This Project Matters

This project illustrates the center’s ability to apply AI to a real supply chain workflow with clear operational value. It combines document intelligence, structured extraction, human review, workflow integration, and continuous improvement in a way that reflects how successful AI solutions are adopted in practice.

It also demonstrates a broader capability that can be adapted to other supply chain environments: turning complex, unstructured business documents into usable, reviewable, decision-ready outputs.

How the Center supports industry partners

The center can work with companies that are exploring AI in supply chain or looking to expand existing efforts. Support may include opportunity assessment, project scoping, prototype development, workflow design, implementation support, and continuous improvement of AI-enabled solutions.

Whether the need involves automation, analytics, document processing, decision support, or operational visibility, the focus is on building solutions that are practical, scalable, and aligned with real supply chain needs.