Case study | Energy

Accelerating Inventory Decisions with AI-Powered Recommendations

Improving inventory matching with intelligent recommendations that evaluate inventory, apply business rules, and surface faster, more consistent recommendations.

Overview

A leading electrical power and distribution provider faced challenges when analyzing inventory and generating timely recommendations to support operational decision-making. 10Pearls developed an AI-powered recommendation solution that enables users to quickly access insights needed to optimize inventory planning and management.

Reduced recommendation time 
from weeks to hours
Faster inventory decisions 
with AI-powered matching

Challenge

The organization needed a more efficient way to evaluate inventory data and generate actionable recommendations. Existing processes relied on manual analysis and fragmented information sources, making it difficult for users to quickly identify relevant inventory insights and make informed operational decisions.

Solution

10Pearls developed an AI-powered inventory recommendation engine designed to make transformer matching faster and more consistent. The solution parses YAML files and job notes, applies predefined rules, and ranks available inventory based on suitability. It also provides explainability around the recommendations to give users visibility into why specific options are surfaced, helping reduce reliance on manual interpretation.   

As the platform evolved, we added natural-language and hybrid search capabilities alongside traditional manual search, giving users more flexible ways to find and assess inventory. Together, these capabilities created a more structured recommendation engine that combines business rules, search, and AI-driven ranking within a single experience.

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