PDF Table Extraction — Structure Tables from Reports
Extract tables from scanned or unstructured PDFs into structured data while preserving merged cells, headers, and complex layouts.
Why it's hard
Tables in government statistics and report PDFs are locked in like images — copy them and the columns misalign and merged cells fall apart.
Ordinary OCR reads only the characters and loses the table's row-and-column structure, so someone has to re-enter it all into Excel by hand.
The DEEP Agent approach
DEEP Agent recognizes tables at the layout level and returns them as structured data while preserving merged cells and header relationships.
The extraction output classifies tables, paragraphs, and headers into categories, so you can integrate it into your systems or review it right away.
Extraction results from real documents
Below are the results of processing real documents with DEEP Agent.
Frequently asked questions
Can it recognize merged cells and complex tables?
Yes. Layout analysis structures the table while preserving merged cells and multi-level header relationships.
Can it process scanned image PDFs?
Because it's built on a Vision-LLM, it recognizes and extracts tables even from scanned PDFs with no text layer.
Which formats are available for extracted results?
Results are returned as structured JSON with per-element categories and position data, and can also be converted to Markdown or HTML.
How accurate is it with Korean tables?
DEEP Agent ranks #1 on OCRBench v2 (English) with a score of 68.1, and is specialized for Korean documents.
Try it with your own document
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