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Built for AI agents and RAG workflows

Turn PDFs into agent-ready Markdown

Raw PDFs break AI agents. BlazeDocs converts PDFs into clean, structured Markdown your agents can search, chunk, quote, and reason over, with API access for OpenClaw, Hermes, MCP clients, and modern RAG pipelines.

Why PDFs break agents

PDFs store layout, not meaning. That means broken reading order, mangled tables, lost heading structure, and unreliable answers when you feed raw PDFs straight into AI.

Why Markdown works

Markdown gives AI systems explicit structure. Headings, lists, tables, and sections survive conversion, so retrieval and reasoning get better fast.

Where BlazeDocs fits

BlazeDocs is the ingestion layer between messy PDFs and the AI stack you actually want to build on top.

Works with your AI stack

OpenClaw workspaces and memory flows
Hermes knowledge workflows
LangChain and LlamaIndex ingestion
MCP clients like Claude, Cursor, Windsurf
Custom RAG pipelines and vector stores
API-first document automation

Direct API, not hand-wavy magic

BlazeDocs already exposes a real conversion API. Upload a PDF and get back structured Markdown plus page and usage metadata. That makes it a practical fit for agent tool calling, ingestion jobs, and developer workflows.

POST /api/v1/convert
{
  "success": true,
  "data": {
    "markdown": "# Document title",
    "page_count": 5,
    "token_count": 4820,
    "processing_time_ms": 3200,
    "file_name": "report.pdf"
  }
}

Best fit use cases

  • • Converting customer PDFs before indexing them in a RAG system
  • • Giving AI agents reliable access to contracts, manuals, and reports
  • • Preparing documents for OpenClaw or Hermes knowledge bases
  • • Replacing brittle PDF parsers in agent pipelines
  • • Building an API-first PDF ingestion layer for your app

Popular integrations

Stop feeding raw PDFs to AI

Keep the PDF for humans. Convert it to Markdown for agents. That is the actual workflow improvement BlazeDocs sells.