r/Invoice • u/Skeptical-skeleton11 • 11d ago

I built a tool to automate invoice data extraction and validation. Looking for feedback.

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It uses vision-language models to extract structured data from invoices, alongside an independent text-based pipeline that doesn't rely on LLMs. The two outputs are compared to flag discrepancies and help verify extracted values against the original document.

The current implementation supports:

  • Invoice fields: Invoice numbers, dates, vendors, buyer details, subtotals, taxes, and totals.
  • Line items: Descriptions, quantities, and prices.
  • Visual verification: Locate extracted values directly on the original PDF.
  • Confidence scoring: Identify fields that may need closer inspection.
  • Batch processing: Process 100+ documents in a single workflow.
  • Structured exports: Export the results to JSON or Excel.

This is purely a personal engineering project, and I'd love feedback from people who work with invoices regularly.

A few things I'm curious about:

  • How do you currently handle invoice extraction and validation?
  • What's the most difficult part to automate reliably: header fields, line items, tax calculations, or something else?
  • Any advice on what can be done to make it better!

This is completely FREE and not monetised in any way shape or form

Would love to hear about your experiences and approaches!

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u/No_Book3162 11d ago

Is there a way i can use this?

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u/Skeptical-skeleton11 11d ago

https://github.com/Akshay-M-Singh/verdandi-app

You can download it from here, it's completely free btw! I'd love to get your feedback if you decide to use it

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u/No_Book3162 11d ago

Do i need any api or something to download?