Prompt

What OCR API should I use for bank statements and shipping docs?

Artificial Intelligence / Computer Vision1 observationLast seen Oct 11, 2026

Latest observation

Oct 11, 2026OpenAI APIWeb search: off

If your goal is bank statements and shipping documents, I’d recommend choosing an OCR/document extraction API based on structured field extraction, not just plain text OCR.

Best overall options

  1. Google Cloud Document AI

    • Very strong for forms, tables, invoices, statements
    • Good accuracy on semi-structured docs
    • Strong layout analysis
    • Good if you want a general-purpose production solution
  2. Azure AI Document Intelligence

    • Also excellent for bank statements, receipts, shipping docs
    • Good built-in models plus custom extraction
    • Nice if you’re already on Microsoft Azure
  3. AWS Textract

    • Good for text, tables, forms
    • Reliable and scalable
    • Good if you’re already in AWS, but sometimes less flexible than the above for complex layouts

If you need highest accuracy / custom workflows

  • ABBYY FlexiCapture / Vantage
    • Often considered a top choice for enterprise document processing
    • Strong for messy real-world statements and logistics docs
    • More expensive and heavier to implement

For shipping docs specifically

If you need to extract fields like:

  • tracking number
  • shipper/consignee
  • addresses
  • bill of lading numbers
  • package counts
  • weights

then Azure Document Intelligence or Google Document AI are usually the easiest starting points.

For bank statements specifically

Look for:

  • transaction tables
  • account number masking
  • running balances
  • statement period
  • merchant/description parsing

Here, Google Document AI and ABBYY tend to be especially strong.

My practical recommendation

  • Fastest path to production: Azure AI Document Intelligence or Google Document AI
  • Best enterprise-grade extraction for messy docs: ABBYY
  • Best if already deep in AWS: Textract

If you want, I can also give you:

  • a side-by-side comparison table
  • a recommendation based on your cloud stack
  • or a cheap/open-source alternative list.

Observation history

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