If you’ve ever tried to extract data from legal contracts, financial reports, or dense PDFs, you already know the pain. You throw a standard OCR tool at a 20-page multi-column document, and it spits out a garbled mess.
Contracts are notoriously difficult to parse. They aren’t just simple top-to-bottom text. They are a chaotic mix of multi-column layouts, dense tabular data, indented paragraphs, and signature blocks.
Standard OCR reads left-to-right, line-by-line. But humans don’t read like that. We read columns, we understand visual hierarchies, and we naturally skip across tables.
So, I built a pipeline that actually sees the document the way a human does. By combining Layout Aware OCR (using Docling and PaddleOCR) with an LLM (via Groq, though you can easily swap in OpenAI or Anthropic), I created a system that cleanly extracts key terms, clauses, and structured data from the messiest contracts.
Check out the detailed article with code examples and a quick startup guide here:
[https://thetechboss.com/ocr-and-llm-pipeline-for-contract-review/]
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