Saving $21M Through AI-Driven Supply Chain Optimization

Overview

A global energy and logistics enterprise required a real-time solution to monitor and forecast lubricant inventory across multiple sites. ImagineX designed a state-of-the-art analytics platform integrating industry sensors, providing 24/7 visibility, proactive alerts, and predictive demand forecasting accessible anytime, anywhere.

Problem

• Limited supply chain visibility created operational inefficiencies.

• Manual gauging and forecasting errors increased safety risks.

• Urgent orders and administrative workload strained resources.

• Lack of proactive monitoring increased risk of inventory run-outs.

• Needed a sensor-agnostic solution integrating multiple vendor devices.

Solution

ImagineX deployed a hybrid cross-location team to design and implement a human-centric web application and end-to-end service framework. The platform ingested IoT sensor data from multiple vendors, ensured API compliance, and leveraged Databricks and Azure for predictive analytics. Role-based dashboards provided transparency for internal stakeholders and distributors, while a custom reorder algorithm and ML forecasting model predicted demand up to two months in advance.

Outcome

• Successfully launched MVP and V1.0, with ongoing onboarding for customers and distributors.

• Projected $21.4M in cost savings over five years.

• Monitored over 6,400 tanks across the U.S. supply chain.

• Enabled visibility and proactive management for 105 companies and 266 active users.

• Demonstrated at industry trade events, driving interest for expansion to additional regions.

Technology Consulting

• Technology Consulting

• Service Design

• Cloud Development

• Data Engineering

Software Team

• Product Manager

• Cloud Engineers

• Data Scientists

• UX/UI Designers

Technologies Used

• Databricks

• Microsoft Azure

• IoT Sensors (multi-vendor APIs)