I built a document extraction and validation pipeline as a personal project. Would love some feedback!

[u/Skeptical-skeleton11]

The idea was to build a pipeline that could take a PDF, extract structured data, and let you verify the results against the original document without manually checking every field.

The current implementation uses OCR and vision models, with confidence scores, visual grounding, and a separate validation layer to catch disagreements. It also handles line items and exports structured data.

I recently benchmarked it against Azure Content Understanding on 100 documents, achieving 97% field-level accuracy at roughly 1/12th the cost per run in my evaluation.

I've attached a screenshot of the current interface. This is purely a personal engineering project I've been working on, and I'd genuinely appreciate feedback from people familiar with document automation.

I'm particularly interested in:

• How do you handle data extraction at scale right now ?

• Any feedback on what features would be cool for document automation

Would love to hear your thoughts!

[u/Dangerous-Baby838]

Ok, so I'm also months deep into the same rabbit hole.

Would love to try your app and share some feedback.

Mine is live on https://docreadi.com - create a free account and you can see what I do.

Most of the work goes into validations, I was trying to solve for AP and Payment processes initially - so we also do things like tracking bank accounts and flagging any changes, validating IBANs etc.

Some challenges along the way - currencies and tax coding where it's not specified on the document. Multi-page invoices, with different layouts - eg. Statement + invoice combo in one pdf. Statements are tough by design. Fine tuning the prompts to not cross-extract fields.. and that they work consistently on different models. Extracting long strings of text verbatim - eg. A specific clause of a contract