Case Study | Energy
AI-Driven Inventory Matching for Smarter Operations
Automating complex matching processes with AI to improve visibility, reduce manual effort, and enable faster, data-driven decisions across operations.
Overview
A leading electrical power and distribution provider faced inefficiencies in manually matching transformer orders to available inventory, limiting visibility and slowing fulfillment. 10Pearls developed an AI-powered application that automated order matching, embedded business rules, and enabled real-time recommendations.
Reduced manual effort
with automated workflows
Enabled faster decisions
with real-time insights
Optimized asset utilization
across inventory
Challenge
The organization relied on manual, spreadsheet-based processes to match transformer orders with available inventory, making operations time-intensive and dependent on expert judgment. Inconsistent business rules across transformer types and conditions led to variability in decision-making and reduced accuracy in order of fulfillment.
Limited visibility into available units and margin opportunities made it difficult to prioritize optimal matches, resulting in missed revenue opportunities and inefficient asset utilization. These challenges constrained the organization’s ability to scale operations efficiently while maintaining consistency and profitability.
Solution
10Pearls developed an AI-powered inventory matching solution designed to automate and optimize order allocation across available assets. The solution introduced rule-based decision frameworks aligned with Internal Review Board (IRB) standards, ensuring consistency and accuracy across matching scenarios.
AI-driven logic enabled intelligent margin calculations and real-time recommendations, allowing teams to identify the best-fit units based on availability, condition, and profitability. The platform replaced manual workflows with a centralized system that provided end-to-end visibility into inventory and order matching, improving decision speed, and reducing dependency on institutional knowledge. By embedding automation and scalable architecture, the solution positioned the organization to support future growth while maintaining operational control and governance.
Customer
Global electrical power and distribution provider
Services
Tech stack
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