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Guides, comparisons, and updates on PDF-to-markdown conversion.
Python Invoice OCR: Extract PDF Invoices to Markdown and CSV
Parse PDF invoices in Python by calling a Markdown API, extracting fields and line items, and exporting structured JSON or CSV.
How to Build a RAG Pipeline with PDF Documents
A step-by-step tutorial for building a retrieval-augmented generation pipeline that ingests PDFs. Uses the pdfToMarkdown API, LangChain, OpenAI embeddings, and ChromaDB — with complete, runnable Python code.
Extract Tables from PDFs in Python as Markdown
Extract PDF tables in Python as Markdown or CSV with a vision API, including scanned PDFs and complex layouts that rule-based parsers miss.
Markdown for LLMs: Format PDFs for Better RAG Retrieval
Good Markdown for LLMs and RAG preserves heading hierarchy, tables, lists, and clean section boundaries for better chunking and retrieval.
The Hidden Cost of Bad PDF Parsing in RAG Systems
Poor PDF parsing silently destroys RAG pipeline quality. Broken tables, lost headings, and garbled text produce bad embeddings, irrelevant retrieval, and LLM hallucinations. Here's how to quantify the damage and fix it.
PaddleOCR vs Tesseract for PDF OCR
Tesseract is the default choice for OCR. But vision-language models like PaddleOCR-VL-1.6 represent a fundamental shift in how machines read documents. Here's why we built on PaddleOCR and what it means for extraction quality.
PDF Parsing in 2026: Tesseract vs PyMuPDF vs Vision Models
A comprehensive comparison of every major approach to PDF text extraction — text-extraction libraries, traditional OCR, cloud OCR services, and vision-language models. Strengths, weaknesses, pricing, and when to use each.
PDF Structure: Why Text Extraction Is Hard
Why can't you just read the text out of a PDF? Because PDF is a page description language, not a document format. Here's exactly what's inside a PDF file, why text extraction is so painful, and what to do about it.
pdfToMarkdown vs LlamaParse for RAG: A Deeper Comparison
Building a RAG pipeline that ingests PDFs? This post compares pdfToMarkdown and LlamaParse specifically for retrieval-augmented generation — framework lock-in, embedding quality, pricing at scale, and side-by-side output from the same PDF.
Document AI Without Fine-Tuning: How Vision-Language Models Changed OCR
Traditional document extraction required templates or fine-tuned models for every document type. Vision-language models like PaddleOCR-VL understand any document out of the box. Here's how the paradigm shifted.
Unstructured Alternative for RAG: When to Swap partition_pdf for an API
Compare an Unstructured alternative for PDF-to-Markdown: hosted VLM OCR, GFM tables, and a keyless demo versus local element-level parsing.
pdfToMarkdown vs LlamaParse: PDF Parsing for LLM Pipelines
Both tools convert PDFs for LLM workflows. LlamaParse is tightly coupled to the LlamaIndex ecosystem. pdfToMarkdown is a standalone API that works with any stack. Here's the difference.
pdfToMarkdown vs Mathpix: Which PDF API Should You Use?
Mathpix is excellent for scientific papers with equations. pdfToMarkdown is the better choice for most developers. Here's how they compare on price, output quality, and ease of use.
Why Convert PDFs to Markdown for LLMs, RAG, and Search
Convert PDFs to Markdown for LLMs to preserve headings, tables, and lists for cleaner prompts, semantic RAG chunks, search, and automation.