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LLM & Document Tooling

PDF to Markdown Converter

Convert PDF files into clean, LLM-ready GitHub-Flavored Markdown. Preserves headings, structured tables, and reading order with single-digit millisecond Rust parsing.

  • High-performance AnyDoc Rust engine
  • Preserves tables, lists & heading anchors
  • Strips binary overhead for 80%+ token savings
  • Private & secure: processed in-memory

PDF to Markdown Converter

Supported formats: .pdf • Up to 25MB

Source Input

Drag & drop your PDF document here

or click to browse your files (.pdf)

Max file size: 25MB

No Markdown generated yet

Upload a document or paste content on the left to see the structured Markdown output.

Knowledge base

Why Convert PDFs to Markdown for LLMs & AI Workflows?

PDFs were designed for printing layouts, not machine comprehension. Converting them to Markdown unlocks significant LLM efficiency.
01

Drastic LLM Context Window Savings

Standard PDFs contain heavy font tables, vector drawing coordinates, and page container metadata. Feeding a PDF into an LLM often exhausts valuable token limits.

Markdown strips away binary visual bloat while retaining only semantic text, code, and tables, reducing token usage by up to 85% and significantly cutting API inference costs.

02

High-Fidelity Tables & Reading Flow

Naïve text extractors turn two-column layouts and data grids into jumbled, unreadable lines.

Powered by Firecrawl AnyDoc, our engine understands layout geometry and converts table grids directly into valid GitHub-Flavored Markdown (`| Col 1 | Col 2 |`), making financial reports and research papers immediately usable for RAG.

03

Zero Persistent Storage Privacy

Your documents are converted in-memory using low-level Rust bindings and immediately streamed back to your browser.

No copies are written to databases, cloud storage buckets, or retained for AI training.

Frequently Asked Questions

Why should I convert documents to Markdown for LLMs and AI workflows?

Binary containers like PDF, DOCX, and XLSX carry massive visual formatting, font definitions, and XML schema metadata that consume valuable context window tokens. Markdown strips away this visual bloat while preserving semantic headings, bullet lists, and tables—reducing token count by up to 85% and significantly speeding up AI inference.

How does the converter handle tables and complex layouts?

Powered by Firecrawl AnyDoc, the conversion engine calculates the physical geometry of spreadsheet grids and document tables, translating them into GitHub-Flavored Markdown (GFM) pipe tables (| Col 1 | Col 2 |). This preserves column alignment and relational meaning without data scrambling.

Does PDF conversion work with scanned images or require OCR?

AnyDoc extracts text directly from digital and vector PDFs with an embedded text layer in single-digit milliseconds. If your PDF consists of scanned pages or camera photos without a text layer, optical character recognition (OCR) is required.

Are my uploaded documents stored or retained on your servers?

No. Document conversions are processed entirely in-memory and the resulting Markdown is streamed immediately back to your browser. Your files are never written to disk, stored in databases, or used for AI training.

What is the maximum file size supported?

You can convert files up to 25MB in size directly through the web interface. For larger enterprise workloads, batch document processing is available via the SpeedVitals API.