A hands-on comparison of two approaches for extracting structured data from B2B order forms: a traditional OCR+regex pipeline using pytesseract, and an LLM-based pipeline using pytesseract, Ollama, and LLaMA 3. The rule-based approach fails when document layouts vary (e.g., 'PO Number' vs 'Order Reference'), while the LLM correctly handles both layouts without any rule changes. The post also covers when NOT to use an LLM — stable/standardized documents, high-throughput needs, regulated industries requiring explainability, and limited infrastructure — framing the choice as a strategic rather than purely technical decision.
Table of contents
1 – Step-by-Step Guide2 – Head-to-Head Comparison3 – When should we NOT use an LLM?4 – Final ThoughtsWhere Can You Continue Learning?136 Impressions