90%+ classification accuracy which can recognise the individual images as small as 13x13 pixel.
Identify the right location for each commodity automatically based on the brand, price and category .
Shorten the analytic cycle significantly via real-time data gathering.
Eliminates the error probability of manual operation and contributes to safety and sustainability.
Take a photo of commodities.
Upload the photo to the system.
The system extracts the data from the photo and validates the task.
Use a rectangle mark to distinguish each commodity and label the SKU name on the top of each rectangle mark.
Output a JSON file which contains all the location information of the commodity.
Simplify store operations and maximise store productivity to deliver a consistent shopping experience free from preventable shelf issues such as out of stocks or misplaced products.
Leverage image recognition technology, in-depth reporting and real-time analytics to uncover at-the-shelf opportunities leading to customer value proposition.
It requires little manual interference that can optimise and adjust its processes through sheer automation, which maintains reasonable overall decision-making and efficiency without managerial oversight.
With relevant data readily obtainable across all levels, automated systems will be able to take note of trends and help retailers make more accurate choices.
Maximise ROI with data-driven execution scheduling and drive precise merchandising tasks via AI technology.
Maintain quality and stability.
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