RetailAI® Fresh

RetailAI® Fresh 

RetailAI® Fresh solves for the time-consuming and error-prone experience that grocery store customers today struggle with when weighing fresh products on a self-serve scale. This solution retrofits traditional scales, enabling recognition of fresh products automatically – even while bagged – significantly reducing mis-click shrink, staff assists, and long queues. RetailAI® Fresh learns and remembers SKUs for self-serve products, enabling large-scale deployment. 

Problems with Today's 
Self-service Scales

Operational Inefficiency

Although the scales and self-checkout system are supposed to be easy to use, customers often turn to store staff for assistance, resulting in high operational costs and long lines. 

Poor User Experience

Paying for fresh produce by weight takes a toll in time and frustration. Finding the correct item on the self-checkout screen takes - on average - more than 3 clicks and more than 15 seconds per item. 


Mis-clicking is common, leading directly to operating losses. Many customers aren't necessarily aiming to shoplift, but the effort to sift through a complex UI may cause them to mis-click out of frustration.

RetailAI® Fresh

RetailAl® Fresh helps retailers increase revenues by reducing mis-clicks and cutting usage time down signficantly, allowing for more usage during peak hours.

RetailAI®️ Fresh
How It Works

Step 1

Shoppers place their items
on the scale. It can be within or without a plastic bag.

Step 2

RetailAl® Fresh identifies the items and offers matching thumbnails for easy 1-click selection.

Step 3

Shoppers follow the on-screen prompts to complete their purchase with just one click. 

Step 4

The system prints a receipt automatically. Likely mis-clicks will optionally print a star on the ticket.

RetailAI®️ Fresh
System Operation Closed-loop

Why RetailAI® Fresh?

Recognition Accuracy

· Works with fruits, vegetables, grains, nuts - even when they’re bagged.
· New SKUs can be added automatically, and the accuracy gets better with every use.

Efficiency Improvement

· Significantly reduces shoppers’ average transaction time.
· Up to 90% reductions in some cases. 
· Fewer, faster lines means a better shopping experience for customers. 

Shrinkage Reduction

· Shrink cut by 50% or more. 
· Provides a platform to better understand customer behavior and paves the way for further shrinkage reductions. 

Case Study

RetailAI® Fresh by Malong Technologies is an AI powered self-service scale solution that integrates state-of-the-art product recognition. Malong’s technology is revolutionary and is currently shipping to stores as one of the earliest waves of innovation being deployed via the Walmart China Omega 8 platform. RetailAI® Fresh provides a proven solution for our customer’s interest in self-service shopping by reducing friction and delivering significant business value.

Significant ROI

The retailer’s own conservative analysis found a 311% annual ROI using this solution, primarily driven by reduction of mis-clicks (asset protection).

Efficiency Improvement

According to the actual data, the customers’ weighing time has been significantly reduced compared with the initial. The weighing efficiency at the peak period has been increased by nearly 40%.

Experience Optimization

By leveraging such advanced technology, Walmart China is able to offer its customers a smoother, faster and friendlier self-service experience while carefully protecting customer privacy. 

What Customers Are Saying

"With a deep understanding of retail needs, and deep integration of leading AI vision technology, Malong's AI product recognition solution for self-service scales is a strong example of a cross-border innovation. It is a great launch for applying cutting-edge technology to retail and contributing to everyone’s daily life!"

Charlene Ma
The Director of Innovation (Omega 8), Strategy and Innovation, Walmart