The use of computer vision–based technologies in the fields of the retail industry has spread quickly since
the global pandemic crisis. The retail AI for product recognition, inventory management, customer behavior
analysis, status monitoring, etc. enhances customers’ shopping experiences and helps retail shops gain their
new sales stably.
INFINIQ has studied computer vision technologies to develop AI algorithms and commercial products
available for the recognition of atypical products, unmanned display stands, user behavior recognition, and
inventory management and provide AI Store Mealy based on the organic integration of retail AI systems.
- Solutions that help small retail shops such as bakeries, convenient stores, supermarkets, etc. to be set as unmanned for 24 hours Shop-in-shop solutions for unmanned services based on existing spaces
- Available to run it at the same time with the counter during the peak time, 10 times on average faster than when a clerk alone calculates Available to sell and settle even without an additional clerk at late night, so possible to go on sale for 24 hours and go out of stock effectively Available to save costs of clerk training for new menu and Point of Sale (POS), helpful for the flexible and efficient workforce management
- Solutions that help more than 660 m2 or so middle and large warehouse-type shops to be set as unmanned for 24 hours Barcodeless solutions available to recognize plenty of goods just by one-time learning, with no other annoying job like barcode sticking
- Available to settle a great number of goods at once to minimize the waiting time by setting no waiting line and increase a faster turnover Optimized for atypical goods as well as barcoded industrial ones to calculate even fruits and bakery at ease Available to expect customers’ intention through their behaviors based on AI technology to provide a proper solution according to conditions leading to flexible workforce management
Back-end System(HEX VISION)
- This system sorts unique purchase-deciding behaviors happening in a retail shop. Unique N behaviors of a customer are sorted and classified depending on the skeleton method. Event notices of long-time door open, trespass in a keep-out area, staying long, customer falling down, etc.
The information on the space around
a shopping stand used to expect the goods inventory The consumption of goods analyzed
to evaluate a product preferred by a customer through CRM