Built on the Produce Floor
How hands-on experience as a Produce Team Leader at Giant Eagle shaped the AI technology behind Expired Solutions.
The Experience
Our founder Lawrence Hua spent 4 months working as a Produce Team Leader at Giant Eagle, gaining firsthand experience with the daily realities of produce operations — shrink, quality checks, markdown timing, and placement decisions.
During that time, he conducted a series of studies using computer vision to explore how AI could address the core challenges produce departments face every day.
Hands-On Experience
CV Experiments Conducted
Produce Types Now Supported
What We Studied
Shrink Reduction
Used computer vision to identify items approaching spoilage earlier than manual inspection, enabling proactive markdowns.
Quality Assessment
Explored AI-based freshness scoring to replace subjective manual checks with consistent, data-driven quality grades.
Shelf-Life Estimation
Studied how visual indicators could predict remaining shelf life, helping staff decide when to mark down vs. when to hold.
Placement Strategy
Experimented with data-driven placement and rotation decisions — where items should go on the floor based on freshness state.
From Floor to Product
Every feature in Xpired traces back to a real problem observed on the produce floor. The AI freshness scoring, the 135 SKU classification, and the markdown timing recommendations all started as studies during this period — and are now implemented in our production system.
Interested in What We Built?
See how these field insights became a production AI platform for grocery retailers.