• High Operating Costs:
  Stellantis Mopar was spending $2.1 million annually to manually manage and classify their parts catalog, leading to significant resource allocation.
• Manual Effort in Classification:
  Classifying parts into groups, categories, and subcategories required immense manual effort to ensure that the catalog was accurate and searchable.
• Need for Automation and Cost Reduction:
  The company needed to automate this time-consuming process to reduce operational costs while maintaining or improving accuracy.

To address these issues, Stellantis Mopar implemented an AI-powered solution through Gen AI Studio:

• Automated Classification Intelligence:
  The platform extracted and classified new parts based on information from existing databases, using past knowledge and current data to streamline the process.
• Knowledge Assistant:
  By using knowledge graphs, the solution helped generate new catalogs with minimal human involvement, reducing errors and human effort by 70%.
• AI-Based Processing:
  This technology allowed for rapid processing of large data sets, ensuring accurate and efficient classification.

• 63% Reduction in Operating Costs:
  Automation of catalog intelligence and workflow processes resulted in a significant cost reduction, with a 63% decrease in annual operating expenses.
• Improved Time Efficiency:
  Data processing times were significantly reduced, leading to a notable increase in productivity levels and faster response times.
• High Accuracy:
  The automated system achieved a high level of precision, consistently delivering accurate results across all generated catalogs, significantly reducing errors compared to manual methods.

• Gen AI Studio
• Knowledge Graphs