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        1. APPROACH

          To achieve this, we leveraged AI Data Cleanser in the following aspects:

          • Data Engineering: Processed, cleansed and passed a high volume of data for approximately 3 million SKUs through the text mining pipeline
          • Neural Networks: Developed an ML algorithm using elements of supervised and unsupervised learning to classify the remaining SKUs based on existing classifications
          • Deployment: This ML based product classification solution was implemented on the cloud using Microsoft Azure

          KEY BENEFITS

          • The solution allowed the client to achieve product to category classification at scale with higher accuracies, providing better insights into revenue and sales opportunity


          • The monthly classification throughput increased by 28x and the total accuracy of product classification shot up to 95%.