Document intelligence that extracts structured data reliably at scale
Causal Labs builds document intelligence pipelines — PaddleOCR, PaddleX, PyMuPDF and pdfplumber — that reliably extract structured data from PDFs, scans and spreadsheets at scale. Delivery has included OCR and parsing pipelines extracting structured fields from financial reports, PDFs and Excel workbooks.
Causal Labs builds document intelligence pipelines — PaddleOCR, PaddleX, PyMuPDF and pdfplumber — that reliably extract structured data from PDFs, scans and spreadsheets at scale. Delivery has included OCR and parsing pipelines extracting structured fields from financial reports, PDFs and Excel workbooks.
Why generic OCR isn't the same as structured data extraction
Off-the-shelf OCR turns an image into text. It doesn't know that the third number in a table is 'total tax' versus 'subtotal', or that a scanned form's checkbox means the field is true. Structured extraction requires layout-aware parsing on top of OCR — understanding tables, form fields and document structure, not just recognizing characters.
How we approach a document intelligence engagement
Requirements gathering
We review real sample documents to identify the layout variation the pipeline will actually encounter.
Build
Layout-aware OCR and parsing pipelines that extract into a defined schema, with confidence scoring per field.
QA & review
Accuracy is benchmarked against a labeled sample set across the real document variation, not a clean best-case document.
What's included
Layout-aware OCR
Table, form and structured-layout recognition on top of raw text extraction.
Multi-format handling
PDFs, scanned images and Excel workbooks handled through a consistent extraction pipeline.
Confidence scoring
Low-confidence extractions are flagged for review rather than silently accepted.
Schema-targeted extraction
Output mapped directly to the structured schema your downstream system expects.
- Production OCR/parsing pipeline
- Confidence-scored extraction output
- Accuracy benchmark report
- Schema mapping documentation
Core OCR engine for text recognition across scanned and photographed documents.
Extends layout and structure recognition beyond raw OCR.
Used for native PDF text and structure extraction where the source isn't a scanned image.
Table extraction from PDFs with defined layouts.
Built OCR + parsing pipelines that extract structured fields from financial reports, PDFs and Excel workbooks.
typical delivery window
Questions about this service
Does this work on scanned documents with poor image quality?
It depends on how poor — we test against your actual document samples during scoping, and we'll tell you upfront if a specific batch quality won't hit an acceptable accuracy bar without pre-processing.
Still manually re-typing data out of PDFs or scanned forms?
Send us a sample document and we'll scope what an extraction pipeline for it looks like.
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