United StatesFood and restaurants2025 – ongoingLamb Weston
AI classification of EMEA procurement spending
Lamb Weston classified procurement spending with over 95% accuracy, according to Mithra
Problem
Lamb Weston's EMEA procurement team had spending records assigned to broad or inaccurate categories. It lacked the internal capacity to clean the data.
Approach
The team exported spending data to Mithra's cloud workspace. Mithra trained classification models around Lamb Weston's taxonomy and enriched records with supplier information. The classified data returned to the existing procurement suite.
Results
Takeaway
The project improved the data feeding an existing procurement system without replacing that system.
Categories
- Size
- Large enterprise
- Industry
- Food and restaurants
- Business function
- Logistics and supply chain
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Vendor solution
- Evidence
- Vendor case study
Sources
Source summaries
Mithra described classifying Lamb Weston's EMEA procurement data and synchronizing the results with its procurement suite. It reported full classification coverage and accuracy above 95%.
Full details are in the original sources.