PDF to JSON
Extract PDF text, metadata and page structure into structured JSON for scripts, pipelines and search indexing.
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About This Tool
When a PDF is an input to a program rather than something a person reads, you need the content as data. Copying and pasting from a viewer does not scale past the second document.
This produces structured JSON: the text of each page, the document metadata - title, author, creation and modification dates, producer - and page-level details such as dimensions and rotation. Text is grouped by page so you can address a specific one rather than parsing one long string.
The output is designed to be consumed directly by a script, whether you are indexing documents for search, feeding text into an analysis pipeline, or checking a batch of files for a particular clause.
How to Use
Add your PDFs
Drop in up to 10 files. Each produces its own JSON.
Choose what to include
Page text, document metadata, page dimensions, or all of it.
Extract
The text layer is read page by page and assembled into the JSON structure.
Download the JSON
Save the file and feed it into your pipeline.
Use Cases
Search indexing
Extract text from a document set to populate a search index.
Automated checks
Scan a batch of contracts for a required clause without opening any of them.
Feeding an analysis pipeline
Structured input for text analysis or a machine learning workflow.
Frequently Asked Questions
Does this work on scanned PDFs?
No. A scan has no text layer, so extraction returns nothing. Run OCR PDF first, then extract.
Is the reading order reliable?
For single-column documents, yes. Multi-column layouts and complex tables can interleave, because PDFs store positioned glyphs rather than logical flow.
Which metadata fields come through?
Title, author, subject, keywords, creator, producer, and creation and modification dates, where the document sets them.
Can I get tables as structured data?
Use Extract Tables for that. It detects table structure and exports rows and columns rather than a flat text run.