Business Impact

  • Cost Savings of ~89% Compared to the Current Process

  • 73% Accuracy for Extraction of Predefined Entities

  • Reduce ~2500 Hrs of Manual Processing Time per Year

  • Additional Field Data Extracted Forms the Foundation for AI/ML Use Cases

Customer Key Facts

  • Location : North America
  • Industry : Insurance

Problem Context

The client is a Fortune 500 insurance holding company in the business of mortgage insurance and long-term care insurance. They sought to automate the extraction of information from Accounts Payable and Claims invoice documents, a currently manual process where the team reviews an invoice, extracts relevant information, and uploads it to a structured database.



  • Large number of documents to index, classify and review manually
  • Poor quality of scanned documents coming from multiple sources like Email, fax, mail
  • Current workflow does not check for invoice duplication and Policy max-outs from core systems


Cloud Vision API
Cloud Functions
Cloud Storage
App Engine
Cloud Firestore


Quantiphi developed an automated OCR and entity extraction solution leveraging Document AI & Cloud Vision APIs to extract predefined entities from AP Invoices. We also built a lightweight user interface(UI) to upload individual/bulk documents & visualize the extracted data.


  • Secure and compliant environment to handle sensitive medical documents
  • Ability to identify invoices that can be processed without human review

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