The customer wanted to create a ‘checkout-free shopping’ experience for its customers. Zippin built Machine Learning (ML) algorithms which can determine what item(s) were picked by customer A, customer B, customer C, …. In order to determine the final price and process check out.

For this requirement, a lot of training had to be done to their ML algorithms which included Item Annotation, Body Part Annotation (elbows, fingers), Torso Annotation, Activity Labelling, and Exception Handling. These training data-sets can range from tens of thousands to few millions.

Intellekt put together a team of 25 ComputerVision (CV) annotators to do the variousannotations using our Annotation and Workflow Platform tool for Computer Vision.All of the annotators are trained and certified internally on AIML basics and tool.Once the ML model achieved considerable confidence, it was moved to Production.Intellekt then was in an engagement to provide Live Support for Exception Handling.This occurs when the model is unable to identify or act per its input.

Over 5.7 million images were annotated till date. There was a 35% Productivity increase after they came to Intellekt. This was achieved because of the platform tools, best practices and processes put in place. We do not just have the annotators putting boxes or annotations, but we understand what is required to support the Data Science teams. We have been working
together for 4 years now!