Blog

Guides, comparisons, and updates on PDF-to-markdown conversion.

· guides

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.

· ocr

PaddleOCR vs Tesseract for PDF OCR

Tesseract is the default choice for OCR. But vision-language models like PaddleOCR-VL-1.5 represent a fundamental shift in how machines read documents. Here's why we built on PaddleOCR and what it means for extraction quality.

· python

Extract Tables from PDFs in Python as Markdown

Compare Camelot, tabula-py, pdfplumber, and a Markdown API for extracting PDF tables in Python, including complex layouts and scanned PDFs.

· rag

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.

· rag

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.

· guides

Markdown for LLMs: Format PDFs for Better RAG Retrieval

Learn how heading hierarchy, table formatting, and clean Markdown from PDFs improve chunking, embeddings, retrieval quality, and LLM answers.

· comparison

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.

· comparison

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.

· tutorial

Python Invoice OCR: Extract PDF Invoices to Markdown and CSV

Build a Python invoice OCR pipeline that converts PDF invoices to Markdown, extracts fields and line items, writes CSV, and handles LLM fallback.

· ocr

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.

· comparison

Unstructured Alternative for RAG: When to Swap partition_pdf for an API

Looking for an Unstructured alternative for PDF parsing in RAG pipelines? An honest comparison — what partition_pdf does well, where its element model and setup cost hurt, and when a markdown API is the simpler choice.

· comparison

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.

· comparison

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.

· guides

Why Convert PDFs to Markdown for LLMs, RAG, and Search

Why Markdown is a better extraction target than raw PDF text for LLM prompts, RAG chunking, document search, and automation workflows.