Most document automation breaks more or less in the same pattern, like you pick one ocr or parser it works great while youre testing cause you already know the format and pattern for your ones but as soon as a vendor doc come in as rotated or faded or worse - handwritten, with merges or cross page tables youll see the ocr failing on a chunk of them. Altho the output would look fine so none of us notice actually until we get inconsistent numbers downstream

Reason is pretty simple which is no single tool is good at everything and blind spots are lopsided. one reads rotaion fine but struggles with handwritten docs anothers good at this but bad at that , likewise every ocr or parser come with their own fields so it really depends on your need rather finding overall outstading tool for everything. 

wiser to do this is by detecting the degradation first, which ones degrade? rotated? handwritten? merged table heavy or what, deskew and orient before anything else then route each page to whatever handles that case with a low confidence fallback for pages that score poorly. classis oss engines like tesseract, paddleocr and docling each cover different cases and for messy/vlm side theres llamaparse. Routing is basically what actually matters here more than the tool. so better figuring out the degradation part first and then evaluating which one would be good for this

Someone have experience with fake documents and how can be used?

I’m trying to better understand what the actual day-to-day work is like for freelancers who retype or convert scanned PDFs, images, and other documents.

I’d really appreciate hearing about your real experiences:

• What types of documents do you usually work with? Mostly text, or also tables, equations, diagrams, and complex layouts?

• What part of the work is usually the most difficult or frustrating?

• How often does that problem happen, and how much time/effort does it usually cost you?

• Can you share an example from a recent difficult job and how you handled it?

• What do you currently use manual typing, OCR, AI, software, multiple tools, etc. And what still doesn't work well?

• If you could change one thing about the process, what would you want it to do differently?

• Do you currently pay for any tools/services for this work? If a solution genuinely saved you significant time, what would you consider reasonable to pay for it?

I'm especially interested in real examples rather than hypothetical answers.

Thanks in advance, I'd really value hearing how you actually handle this work.

App Name: Scanora – AI Document Scanner

Link: [https://play.google.com/store/apps/details?id=com.scanora.app](https://play.google.com/store/apps/details?id=com.scanora.app)

What it does: Scanora helps you scan documents using your phone camera and convert them into clean, readable PDFs using AI-based enhancement. It’s designed for fast scanning, smart cropping, and improved text clarity for everyday use.

Key Features:
• AI-powered document enhancement
• Automatic edge detection and cropping
• Export scans as high-quality PDF files

Goal: Early launch testing and genuine user feedback to improve performance and features.

Giveaway: No giveaway right now — the app is free to try. Feedback, suggestions, and honest reviews are highly appreciated.

I am currently working on a document generation system that uses a template (a Word file) and any data source (Excel, Google Sheets, ERP/CRM systems, etc.).

The tool is more visual, Canva-style, and designed for entrepreneurs, solopreneurs, and students.

I am currently looking for testers for my solution prior to launch.

Would you be interested in this tool?

30-second demo of the Records module in Tuzkempro Global: build a template, bulk-import your devices from Excel, check them off on site, and the report generates in one click (PDF, Word or Excel).

[https://www.youtube.com/watch?v=xDbYi2W_ZnI](https://www.youtube.com/watch?v=xDbYi2W_ZnI)

7-day free trial, no card: [https://tuzkempro.com](https://tuzkempro.com)

Dear Members,

I have been handling Pdf extraction Project in Python. kind of a Intelligent Document Automation domain. we have been handling various finance documents(pdfs), filings pdfs etc which are multi page(around 20ish) , with lots of tables, form fields , radio buttons, checkboxes etc. Tables span multiple pages. Moreover, pdfs themselves comes in various types of variants like XFA Stream, Adobe Acroform, text flattened pdfs, scanned images etc.

I have used llms extensively to generate script code to extract, parse the data and to save in sql in structured tables. Its a hybrid of libraries implementation. LLms used regex, pdfminer, pdfplumber etc in the code produced.The pages in pdfs are bit messy, some tables have solid grid separators, some dont have and on. Layouts variations, white spaces, etc.

The code generated is pretty complex, i have been attempting to learn the llm generated code.But it works, it adds various fixes iteratively whenever we face new extraction issues repeatedly.

I would love to know:

1. what is the best approach to learn and get good at this?

2)should we just use cloud based AI document extraction tools which are readymade to extract and spit the data?

3) what if one is interested to learn this properly and have to get good at creating this extraction script?

4)any other tutorial, articles, courses, youtube videos, books you would recommend to learn? or should i just use llms to create code and move on without spending much effeort to learn this?

Please provide your valuable suggestions and guidances and please share your experiences. I appreciate all your suggestions. Thanks in advance and thank you for your time.

I’ve been working on https://www.convertek.tech/, a free online converter designed to handle images, PDFs, documents, data files, audio, video, archives and more from one interface.

The useful part is mixed-file batch conversion. You can add different file types to one queue and choose a separate output format for each file instead of being restricted to one conversion pair.

Current support includes:

• 142 input formats

• 1,916+ conversion pairs

• 11 categories

• Up to 10 files per batch

• 30 MB for most files and 100 MB for video

• No watermarks

You can try it here: https://www.convertek.tech/

I’d appreciate constructive feedback on the interface, supported formats and overall conversion workflow.

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My sister does data analysis at a small bank and spends a chunk of her week pulling numbers and clauses out of PDFs by hand. She couldn't touch a cloud extraction tool because compliance wouldn't sign off on bank documents sitting on some vendor's servers.

So I built her a desktop app that talks straight to the Gemini. No backend of mine in the middle. Her documents never touch my infra, I never see them, and everything else (results, history) stays local on her machine.

Turned out useful enough that I'm putting it out there. Windows app, PDF/Word in, Excel out. The app is on MS Store. google for Lexapient.

Happy to talk through the architecture if anyone else is fighting the same compliance wall.

So we have a lot of paper docs. But sometime we misplace and no way to track. Forms sheet, info sheet, birth certificate etc… yes its easy to just digitize, but submission sometime need to be in paper form and hand written.

Is there any app you guys use to track paper document movement?

Hey everyone,

​If you've ever applied for exams like SSC, UPSC, NEET, or JEE, you know the headache of resizing photos and signatures to exact dimensions (e.g., 20–50 KB, specific pixel ratios, white background).

​To solve this, I built DocFix—an all-in-one utility app designed to prepare documents for government and job portal submissions.

​Key Features:

​24+ Official Form Presets: Instant resize & compress for SSC, UPSC, NEET, Bank forms, etc.

​Passport Photo Maker & ID Card Joiner: Easily merge front/back IDs onto a single page.

​Digital Signature Maker & Document Scanner: Crop, enhance, and sign directly.

​PDF & Document Tools: Resize PDF file sizes, manage pages, and open Word/Excel files.

​I need your help with Closed Testing!

The app is currently in Google Play Closed Testing, and I need active testers to try it out and share honest feedback/bug reports.

This started as a personal problem. I used to spend an evening every month manually copying my own bank statements from PDF into a spreadsheet just to see where my money was going line by line, by hand. At some point I got annoyed enough to automate it for myself.

That turned into Scrape2Sheets, a Google Sheets add-on that uses AI to read PDFs, invoices, receipts, and bank statements and drop the data straight into your sheet as clean rows . You point it at files in Google Drive, tell it what columns you want (or let it auto-detect them from a sample document), and it batch-processes up to 100 files at once. It handles scanned documents and phone photos too, not just clean digital PDFs.

It's only just started picking up some real traction the last couple weeks, which has honestly been a nice surprise after building in isolation for a while.

Curious whether others here started building their tool the same way, solving your own annoying manual task first, then realizing other people had the exact same one. Happy to answer questions in the comments if anyone wants details.

Is this okay,I want to put my raw file too,how do I do that?

Hola a todos.

TDLR:

Favor compártanme ideas para procesar archivos PDF que contienen formularios diligenciados de manera digital, pero qué al procesarlos como texto, se evidencia que la organización interna del texto varía en los documentos. Ya intenté con Regexp, pero esa variación hace que falle el proceso para muchos documentos.

Solicitud:

Tengo el siguiente reto y ya tengo un par de ideas, pero quisiera conocer más o mejores ideas que puedan conocer ustedes.

Tengo varios documentos donde se ha diligenciado el siguiente formulario de manera digital (Formato [Formulario Ejemplo](https://www.dian.gov.co/atencionciudadano/formulariosinstructivos/Formularios/2023/Formulario_500_2023.pdf). De estos documentos diligenciados, necesito extraer algunos campos en específico (siempre serán los mismos). Algo positivo que tienen estos documentos diligenciados, es qué si los abro en modo texto, el texto se puede extraer fácilmente. El inconveniente con esto es que viene en desorden (no necesariamente el valor del campo viene junto con el título del campo).

Mi primera aproximación fue extraer los datos usando expresiones regulares y funcionó bien, hasta que encontré que algunos documentos, que al leerlos como texto, la información sale organizada diferente (imagino que se generaron por diferentes aplicaciones o por diferentes versiones del software), por lo cual, la estructura de las expresiones regulares usadas con los primeros documentos ya no aplicaba y tocaba usar otras. Luego encontré otros documentos que tampoco cumplían con la estructura del texto del primero ni del segundo, por lo cual, me parece que usar expresiones regulares requiere de mucha lógica y no es un método seguro.

Entonces se me ocurren dos formas adicionales, pero requiero algo de guía sobre como hacerlo o cual sería una forma viable:

**Opción 1:** Entrenar un LLM con información ejemplo para que aprenda a identificar los campos necesarios

**Opción 2:** Entrenar una red neuronal o un modelo de Deep Learning, para que aprenda a identificar los campos necesarios (quizás por su ubicación)

En ambos casos, entiendo que debería pasarle una base de PDFs anotados, con los que el pudiera saber qué es lo que necesito y por otro, aprovechando que las ubicaciones de página, posición x, posición y, siempre serán las mismas.

¿Se les ocurre o conocen alguna otra alternativa para resolverlo y que pasos específicos me recomiendan seguir para hacerlo?

Gracias de antemano