Document extraction
Your PDFs become data.
Drop in a PDF, native or scanned: the tool reads it and hands back the key facts as structured data, right next to the original.
What the tool does.
Text is pulled straight from the PDF when it can be; when it cannot, optical character recognition takes over. A language model then picks out the fields that matter.
You choose which fields to expect for each kind of document: invoice, lease, listing, report. The model runs on the tool’s own server, so the document is never sent to an outside service.
- Native and scanned PDFs (character recognition)
- Fields returned as structured data
- Document and result shown side by side
- A choice of language models
- The model runs locally, with no outside service
How it works.
- 01
Drop in the PDF.
- 02
The tool reads it, using character recognition if it is a scan.
- 03
Check the extracted fields against the original, then take the data.
Where AI comes in · AI inside
AI inside: a locally run language model extracts the fields from the text. A person still checks the result.
The other addresses.
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Name it. We’ll handle the rest.