PDF to text converter forscanned and complex documents.

Extract clean text from scanned PDFs, tables, and multi-column layouts in under 2 minutes.

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Built for legal docs, financial statements, and research PDFs

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Completed conversion sample

# Lease Agreement
**Landlord:** John Doe
**Tenant:** Jane Smith

| Term | Detail |
|---|---|
| Monthly Rent | $1,850.00 |
| Start Date | January 1, 2025 |

How it works

Step 1

Upload your PDF

Up to 200MB per file.

Step 2

Review free preview

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Step 3

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$1 AUD per conversion.

See the difference

The left is typical extraction noise. The right is structured output ready for humans and AI workflows.

Other tools
LEASE  AGREEMENT

Th1s |ea$e agr€€m€nt €nt€r€d
into by and b€tw€€n :

LANDLORD :  J 0 h n   D o e
T€nant:  J a n €   S m i t h

M0nth|y R€nt: $ 1 ,85 0 .00
St@rt  D@te: J@n  1  2025
T€rm:  1 2   m 0 n t h s

Uti|iti€$:  T€nant r€sp0n$ib|€
D€p0$it:  $ 3,7 0 0.0 0
Unpapered
# Lease Agreement

This lease agreement is entered into
by and between:

**Landlord:** John Doe
**Tenant:** Jane Smith

---

| Term          | Detail           |
|---------------|------------------|
| Monthly Rent  | $1,850.00        |
| Start Date    | January 1, 2025  |
| Lease Term    | 12 months        |
| Deposit       | $3,700.00        |

Tenant is responsible for all utilities.

Built for hard PDF extraction cases

Scanned PDFs

Image-based documents are OCRed and reconstructed into readable text instead of broken symbols.

Tables preserved

Nested rows, merged cells, and statement tables are preserved in clean markdown output.

Multi-column order

Two-column papers are extracted in correct reading sequence for usable downstream text.

Real-world before and after examples

Legal trust deed

Before

Broken OCR names, scattered clauses, unreadable signatures section.

After

Structured clauses and parties preserved in clean markdown.

Bank statement

Before

Transactions collapse into one long line with missing columns.

After

Rows remain readable and ready for CSV or spreadsheet cleanup.

Research paper

Before

Two-column text merges out of order with references mixed in.

After

Reading order is reconstructed with headings and sections intact.

Operations SOP

Before

Step lists and table references lose context after copy-paste.

After

Steps, labels, and document hierarchy are preserved for reuse.

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Frequently asked questions

What makes this different from copy-pasting?
Copy-paste loses reading order, breaks tables, and fails on scanned pages. Unpapered reconstructs document structure before output.
What types of PDFs does it handle?
Native text PDFs, scanned image PDFs, and mixed documents. It is built for difficult layouts.
What output formats are available?
Markdown (.md), plain text (.txt), and JSON (.json).
How large can my PDF be?
Up to 200 MB per file, with up to 20 files in one batch upload.
How is my data handled?
Inputs are deleted after processing. Outputs are retained for 24 hours, then deleted automatically. Files are not used for model training.
How long does conversion take?
Most jobs complete in 30–90 seconds. Large scanned files may take longer.
Do I need an account?
No account, no sign-up, no email required.
What happens after I upload?
You get progress updates and a free preview. Full downloads can then be unlocked for $1 AUD per conversion.