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AI Powered Product Sorting for Robotic Systems
AI Powered Product Sorting for Robotic Systems
High volume operations increasingly rely on automation to keep pace, but manual sorting remains slow, costly, and prone to error. To help our client explore a smarter alternative, we developed a computer vision model that allows an existing robotic arm to identify, classify, and sort products with accuracy and speed.
The Challenge
The Challenge
The client wanted to test whether a robotic arm could sort different fruit types automatically. To do that, the robot needed “eyes” — a vision system capable of recognising each item and triggering the correct pick-and-place action.
The challenge was enabling accurate real time identification across multiple fruit categories.
The Solution
The Solution
AC SmartData built a deep learning vision model. The model provides fast, reliable classification and sends that information to the robot’s control system.
In short, we created the intelligence layer that allows the robot to:
see the item → identify it → sort it correctly.
The Results
The Results
The proof of concept delivered strong performance:
90%+ classification accuracy across fruit types
Consistent recognition in varied lighting and positioning
Smooth integration with the robotic arm’s existing control workflow
This demonstrated that AI Vision can significantly improve sorting reliability without requiring changes to the robot hardware.
Conclusion
Conclusion
By adding a deep learning–based vision system to an existing robotic arm, our client gained a clear path toward faster, more accurate sorting operations. This approach is applicable across manufacturing, agriculture, recycling, logistics, and any environment where items must be identified and sorted at speed.
We continue to expand this technology to support more complex product types and real world industrial conditions.
Improving Product Discovery with AI Image Recognition
Improving Product Discovery with AI Image Recognition
In online retail, customers expect to find the right item quickly — and when the search experience fails, so do sales. Clothing retailers in particular struggle with visual similarity: two products may look nearly identical, but only one matches the customer’s budget or style. When shoppers can’t easily see their best options, they either overspend or abandon their search altogether.
The Challenge
The Challenge
Our client, a growing e-commerce, noticed a recurring problem: customers were buying high-priced items simply because they couldn’t find similar, more affordable alternatives the store already stocked.
This created two issues:
Missed opportunities to match customers with the right products
Lower customer satisfaction when shoppers realised cheaper options existed
They needed a smarter, more intuitive way to connect shoppers with visually similar products — beyond what keyword search could do.
The Solution
The Solution
We built a deep learning powered image search engine. When a customer views or searches for an item, the engine instantly returns the closest visual matches, including lower priced alternatives. This gives shoppers a far more intuitive discovery experience:
See → compare → explore → choose.
The Results
The Results
After integrating the AI image engine, the retailer saw immediate benefits:
Higher product discovery accuracy — customers reached the right items faster
Increased conversions — fewer dead ends in the browsing journey
More revenue uplift — customers were exposed to similar options they hadn’t found before
Better customer experience — shoppers felt confident they were seeing all relevant choices
The system also surfaced more affordable alternatives, which lowered average order friction while increasing total revenue.
Conclusion
Conclusion
AI driven image recognition reshaped the retailer’s product discovery experience. By understanding products visually, the platform made it easier for shoppers to find the right items at the right price.
This approach is scalable across fashion, homewares, beauty, and any e-commerce environment where visuals drive buying decisions. It reduces search frustration, lifts conversions, and helps retailers get more value from their existing catalogue.
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