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AI Reduced Inventory Cost from $25 Million to $9 Million for a Global Manufacturer

About Our Client

Our client is known for their reliable and high-performing trucks, buses, and passenger vehicles. With 100+ warehouses in different regions of the country, they fulfill the need of spare parts to service centers and fleets worldwide.

The Need

Our client follows strict SLAs to meet each and every customer’s needs on time. However, the biggest challenge in meeting those SLAs occurred when they could not track products running out of the shelf and those in excess quantity. To avoid this situation, they purchase spare parts in advance, even those not in demand making it hard to sell them out. As a result, their inventory cost reached $25 million while delivery commitments were still not met.

Our Solution

Softude developed an AI solution for inventory optimization. It works on past transactional and historical data, analyzes consumers’ purchasing habits and market trends to identify the future demand of each spare part. Through predictive analytics, it also tells when to re-fill the shelves, and which spare part is wasting their inventory space.


  • Inventory holding cost went down from $25 million to $9 million in a few months.
  • 28% saved on purchase of new spare parts.
  • Up to 50% less errors in determining stock requirements.
  • 92% SLA met with on-time delivery.

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