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.

Supermarket image annotation example
Supermarket data annotation Supermarket image annotation example

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Our Services FOR RETAIL COMPANIES include

Retail Annotation


Retail Data Labeling


Retail Data Validation


Retail Data Classification


Retail Data Collection

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

Annotated Bounding Box for Retail
Annotated Skeletal for Retail
Annotated Polygon for Retail
Annotated Segmentation for Retail

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:

Image Annotation for Retail Stores
Retail Store Image Annotation for Retail Stores

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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

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