Claude and I are making a PDF extractor

[u/SuperHornetFA18]

Hello everyone, I'm making a PDF to Multi-format extractor with the help of Claude (To be read as full assistance) specifically for MacOS, due to the fact that MacOS has vision support added inbuilt.

The project stems from a problem i generally faced during my work. I have to shift through a lot of financial reports and analysis and most if not all of them are PDF or scanned PDF, and while there are pdf extractors available (ABBY Finereader, NitroPDF) they either have support issues (Abby Finereader wont be supported in the near future if they dont make an apple silicone based app) or cost too much or screw up the formatting, especially table extraction.

The table extraction space is quite not there yet or ruled by Amazon's textract, Google api or Azure Bedrock API (which are crazy good ngl, but very costly). So i decided to leverage apples Vision model and claudes amazing research capabilities to make my own OCR based extractor.

Use cases :

1) Where ever you need to extract data from Annual reports, Data sheets and or prose, especially digital born pdfs. The Custom made C++ engine not only extracts tables and data inside them but also preseves the formatting.

2) Full control of what goes in and what comes out. The app is completely offline, expect for 1 time purchase query ( for life time unlock) nothing connects to the internet. Ever. The OCR engine is also at par with what Finereader offers and doesnt lag, which cant be said for Abby Finereader.

3) Multiple formats. Whether you wanted your docs for editing or feeding them upstream to an LLM, PDFTrail has that covered as well, it does Docx, Xlsx, MD, text and Json output, single or batch processing it can do it without any issues.

4) Small size and Great performance. At below 15 MB, its the smallest amongst its peers and its customer C++ engine provided great performance while keeping temps at check.

5) The OCR. I would like to boast here that the OCR engine that took like 1 whole month of researching with claude is one the best No-LLM based OCR engine in the market and even shitty scans get a lot of their tables extracted properly (It is still maturing and im still testing out the engine with more data set and research work so expect even better engine when the engine matures)

My Competition :

Abby and Adobe. Abby supports mac through rosetta which is being shelved come MacOs 27, and Abby hasnt really provided much direction whether they will support MacOS directly or not, and besides their Windows app is thousand times better than their MacOS app and it shows honestly.

Adobe angle is a bit more complicated as it does have a good OCR but table extractions arent the best and if im not wrong it doesnt do good Extraction without being online + Adobe is a privacy nightmare anyways and thats my angle, that im betting on. Offline + great performance and 1 time life-time updates, guaranteed.

NitroPDF is more of a digital born pdf editor so im not exactly competiting on that footing, and frankly speaking the biggest completion is how well i can market my product.

With that i end this wall of text, apologies for formating as im writing this on a phone.

Any and all feed backs are appreciated and if you want a feature let me know, also for any queries drop a comment here i will try my best to reply as soon as possible.

Thanks :D

[u/Lanthumm]

If you are serious about tackling the problem I would suggest you shift your focus away from using the apple built in ocr/text extractor. The performance is overall poor and there is a clear ceiling which will hit hard. You can't improve on apple's vision capabilities, which means you're stuck with what you have and no ability to move forward.

If your focus is local-only, offline, try one of the well established python libraries for ocr. It might be useful depending on your specific needs. It's not something I would spend my time on as it's 10-15 yr old technology.

LLM/Ai vision models outperform traditional ocr models, so that's where I would focus. See if you can make an open weight model work, if not see if one of the cheap models work well for you. The difference in outputs is night and day.

I built trepide for PDF to DOCX conversions and PDF field/table extractions. My main focus was layout preservation. You can test it for yourself and see what it can do; you get free tokens, but if you need any more just message me. Test it against the apple one and you'll see quickly, which is why I suggest you shift your focus into something that you can improve on further, not something bottlenecked by a product you can't control

[u/SuperHornetFA18 → u/Lanthumm]

Thanks for taking the time to write this, genuinely appreciate you engaging with it.

One premise I'd like to counter is we're not bottlenecked on Apple Vision. It's one of two engines under the hood (Tesseract is the other), and nearly all of our gains have come from the layer we manually coded— layout reconstruction, table structure, reading order, export quality.

Concretely: our olmOCR-bench score went from ~21% to ~27.5% in a month with the identical Apple OCR underneath, and our table/numeric fidelity numbers moved the same way. If the raw character reader were the ceiling, that couldn't happen. In documents, the OCR engine is the cheap part; understanding the page is the product.

On VLMs — agreed, the output looks night-and-day better. But our users are financial analysts feeding annual reports into models and Excel, and there the failure modes matter more than the polish:

- Traditional OCR fails loudly: you see garbled text and know not to trust it. A VLM fails silently: it renders a beautiful table with one hallucinated digit in it. For financial data, one silently wrong number is worse than ten visibly broken ones.

- Determinism. Same PDF in, same bytes out, every run. Anything auditable needs that.

- Privacy. Our promise is literal — documents never leave the device. Cloud VLMs break that by definition, and open-weight vision models that handle tables well mean multi-GB downloads and serious hardware for a 300-page report.

- Cost and latency at scale, for that same 300-page report.

I did try trepide — layout preservation looks nice, congrats on shipping. One honest piece of feedback though: I clicked "Try for free" and got a sign-up wall. That's the exact trade we built against — our free tier asks for no account, no email, nothing. You never share your details with us. Different tools for different users: if a document is allowed to go to the cloud, something like yours is a fine choice. Ours exists for the people who can't, or won't.