
TL;DR Summary:
Hammoq AI helps Goodwills and thrift stores automate the entire process from donation door to the placing items on the retail floor—reducing the time spent to sort, select the attributes and condition, determine the price point, and print out a labe based on machine learning trained on each store's sales history.
Of the resale industry's nearly three million computers used for donation receipting and back-of-house data capture alone, perhaps the most volatile—and important—resale process remains unaffordable for donated merchandise.
Right now, most stores rely on human instinct, volunteer labor, and rough price charts to assign values. But when you’re receiving hundreds (or thousands) of donations daily, even experienced staff can’t catch every hidden gem—or price each item with pinpoint accuracy. This leads to underpriced inventory, overlooked value, and lost revenue.
That’s where Hammoq AI steps in to transform operations from the ground up.
Hammoq uses machine learning trained on your store’s own historical sales data—not generic resale rules—to automate the entire journey from photo to price tag. Whether it's a pair of vintage Levi’s or a mid-century modern lamp, the system can identify the item, assess its condition, and apply performance-based pricing logic within seconds.
How It Works – A Real Example:
Let’s say a donated pair of Levi’s jeans arrives at your sorting station.
A staff member snaps a photo using the Hammoq app.
The AI instantly recognizes:
- Item type: Denim Jeans
- Brand: Levi’s
- Gender: Men’s
- Size: 34
- Condition: Good
- + More if you have specific requests for your tag
Hammoq then analyzes your store’s own historical sales data and sees how Levi’s jeans perform:
- In fair condition: $6.99 – lower ASP and high-turnover
- In good condition: $12.99 – strong margin and reliable turnover
- In excellent condition: $19.99 – good ASP and strong sell through