Machine learning with neural networks for invoice processing

Case Study

The client is an organization that utilizes professional services from various vendors which results in a huge number of invoices to be processed on a daily basis. They required a system to automate this process to eventually reduce human effort.


  • The customer had to manually review invoices and ensure whether they meet compliance norms, SLAs, and other compliance regulations.
  • Time-consuming to process the barrage of invoices and data that needed to be processed daily.
  • Staff productivity went down due to an increasing number of invoices.

The Zerone approach:

The experts at Zerone created a machine learning invoice processing application and trained it using customer’s historical data. Deep learning techniques allow the application to enhance its self-learning capabilities using neural networks. The resulting invoices are tagged into separate categories for easy processing. The custom application that was developed eventually reduced the need for human intervention and increased productivity, efficiency, and customer satisfaction.

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