State-of-the-art Product Recognition
from any camera feed.
Neurolabs provides Artificial Intelligence solutions for the retail industry, specifically targeting on-shelf monitoring and automatic (cashierless) checkout.
We are building the best product recognition system in retail based on Computer Vision and Deep Learning.
Weight Scales Automatisation
We all went through the painful process of finding the exact type of oranges in a menu of 200 fruits and vegetables.
Neurolabs provides an add-on solution to existing Scale systems, offering automatic product recognition.
The user is presented with a pre-selected menu reducing their interaction with the scale system to a single click.
Self-checkout in Cafeterias
Lunch hours are the busiest time of day for cafeterias. Queues are long and getting a sandwich just takes too much of your lunch break. Using Neurolabs Zia checkout, your employees can focus on delivering a great service leaving the checkout process to us.
We integrate our solution directly with the clients’ existing POS systems in order to smooth the checkout experience and speed up the process. Our algorithms allow us to automatically recognise all products on the tray, presenting the user with the receipt in little to no time.
Our discrete in-store camera solution provides retailers with on-site intelligence by monitoring the availability of each product on the shelf. The teams’ extensive experience in Computer Vision gives us an edge on the competition when it comes to image segmentation and classification.
The relevant information for the retailer can be accessed directly via a smartphone with our one-click solution.
Assisted Self-Checkout in Supermarkets
Shrinkage at self-checkouts is a notorious problem for retailers, with figures north of 4.5$bn worth of loss reported in Australia.
We address specific issues occurring at the checkout tilt, such as scanning the wrong bar code or missing to scan some items. Our camera add-on solution integrates seamlessly with existing self-checkout system and acts as a double check for everything that is checked out.