Automotive AI Cost Optimization
This AI solution uses AI and AutoML to analyze procurement, logistics, and production data across the automotive value chain, optimizing supplier selection, freight routing, and manufacturing quality decisions. By dynamically factoring in tariffs, sustainability targets, and defect risks, it reduces total landed cost while maintaining reliability and environmental performance.
The Problem
“Your supply chain decisions are raising costs because they can’t see risk, tariffs, and quality in real time”
Organizations face these key challenges:
Procurement, logistics, and production teams each optimize locally, driving up total landed cost
Analysts spend weeks in spreadsheets reconciling ERP, MES, and logistics data just to answer basic cost questions
Routing and sourcing decisions can’t keep up with changing tariffs, lead times, and disruption risks
Quality issues are caught late, after defects have already created scrap, rework, or warranty claims