How to Build a Robust OCR Pipeline That Makes Scanned PDFs Searchable

A technical walkthrough published on DEV Community outlines how to design an OCR pipeline capable of converting scanned PDFs into searchable, chunked text for use in retrieval-augmented generation (RAG) systems. The approach processes documents page by page in concurrent batches, allowing natural checkpoints, citations, and parallelism while respecting OCR provider rate limits. The pipeline emphasizes preserving document structure — such as headings and tables — since flattening content degrades both searchability and downstream chunking quality. Quality checks are built in to detect blank pages, rotated scans, repeated headers, and language shifts, ensuring cleaner text and more accurate embeddings. The article was authored by Pranjul Rathour, a GenAI engineer and CTO at SCULT INDIA based in Kanpur, India.