AI applications in retail

What Keymakr can do for you

Keymakr is an expert in providing retail annotations and creating training datasets for retail applications for building machine learning models and visual AI.

We specializes in custom-made Training Datasets for Machine Learning models and Computer Vision AI. We work with any video or imagery data.

AI in retail has the potential to revolutionize the shopping experience by reducing workloads for staff, aiding loss prevention and improving the customer experience. Keymakr’s experienced managers and innovative annotation platform can ensure that AI retail solutions reach their full potential.

Move the bar to see the annotation magic happen

Our Services FOR RETAIL COMPANIES include

Annotation

Labeling

Validation

Classification

Data Collection

The retail annotations are performed by our in-house employees - trained professional annotators.
The retail training data sets go through 4 layers of quality control to ensure the highest quality of the results
All retail annotations could have different precision levels up to “pixel-perfect”

Retail Video and Image annotation types

We can create new types based on your specific requirements. Our proprietary annotation platform features the full range of annotation techniques, including image segmentation. Our skilled annotators are familiar with all annotation tools and are capable of delivering high quality data for your artificial intelligence retail solutions.

Common use cases for the Retail Training Datasets we create:

Move the bar to see the annotation magic happen

Loss prevention – smart checkout

Smart checkouts are an important part of the robotization of stores. They have the potential to minimise theft by monitoring checkouts in real time and providing security staff with information
Accurately monitoring each item passing through the checkout requires pixel perfect image annotation in training data sets

Real-time view of store and field performance

Receive a real-time situational alerts about what’s happening on the shelf, like missing products or empty spaces
Identifying low shelf share in the store
Inventory management
Planogram improvements
Instance segmentation annotation powers this technology by allowing AIs to distinguish between individual items

Sentiment analysis

Analyze facial expressions to understand customer sentiment towards the promotions and products on shelves
This promising use case of machine learning in retail is made possible by video annotation with skeletal annotation techniques
Keymakr’s annotation platform allows video footage to be annotated accurately and efficiently

Analyzing in-store traffic

Map shoppers’ paths around the store to optimize the placement of products and promotions
Capture rate of pass-by traffic and measure how many shoppers walked through the store, which measures promotions capture engagement and gives you a better view of promotional insights

Face recognition

Identify regular customers, reward loyal customers who frequent the store and spend time in it
Remembering customer’s purchasing history and preferences for making personalized product recommendations specific to each client
Facial recognition technology is made possible with key point annotation that identifies facial features in AI training images
Professionally managed teams can annotate video and image data of customer expressions to pixel-perfect levels of detail