Automating Sales Invoice Data Extraction with AI Document Intelligence

GEA processes a high volume of sales invoices and delivery documents, the data from which was being read and stored manually by staff. This was a slow, labour-intensive process with inherent risk of human error. This engagement introduced Azure AI Document Intelligence with OCR capability to scan PDF invoices automatically, extract structured data fields, and make that data available for reporting and analysis.

Customer Profile

GEA is an international company that provides high-quality processing equipment and technology for the food, beverage, and pharmaceutical markets. They help businesses handle complex production demands by offering individual machines, complete factory setups, advanced tech solutions, and full-service support.

Customer Requirement

Sales invoices and delivery documents were arriving in PDF format and being processed entirely by hand. Staff read each document, identified the relevant data points, and entered them manually into storage, a process that did not scale with document volume and introduced significant risk of transcription errors.

No automated mechanism existed to retrieve data from these PDFs or make it available for analysis. The requirement was to replace this manual process with a solution that could scan incoming invoice documents, accurately extract key data fields, store them in a structured format, and enable reporting on that invoice data without any manual handling.

Our Solution

  • Azure AI Document Intelligence with OCR capability deployed to scan and read sales invoice and delivery document PDFs automatically, without manual intervention.
  • Key data fields extracted from each document and stored in a structured format for downstream use:
    • Invoice date
    • Customer information
    • Products delivered
  • Extracted data structured and made available for reporting and analytical use, enabling GEA to query and analyse invoice data at scale for the first time.

Benefits

  • Invoice data that was previously captured by hand is now extracted automatically, removing the manual effort from the process entirely.
  • Structured extraction eliminates transcription errors introduced by manual data entry, improving the reliability of invoice records across the business.
  • Invoice details including dates, customer information, and products delivered are now available for analysis and reporting without any prior manual preparation.
  • The solution scales with document volume — processing capacity is no longer constrained by the number of staff available to handle invoices manually.