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FineParser is a self-hosted document parser for AI pipelines. It runs as one Docker container on CPU hardware and exposes a small REST API: submit a document, then download its structure and text as DocLang, JSON, or plain text. No cloud account, no GPU, and no document data leaves your infrastructure. It is built on the ABBYY FineReader Engine recognition core, packaged for developers who want production-grade parsing without an SDK integration.

Quickstart

Run the container and parse your first document in under five minutes.

Configuration

Recognition mode, languages, and ports.

REST API

Submit a document, poll the job, download the result.

Output formats

DocLang, JSON, and plain text.

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What it does

FineParser recovers a document’s structure, not just its text: tables (including borderless ones), multi-column layouts, headings, reading order, and hierarchy. Handwriting, checkboxes, and images are recognized alongside the text. The output is ready for RAG ingestion, agent workflows, or LLM prompts.

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Why teams use it

  • Keeps tables, columns, and headings intact, and tells you where each one is on the page.
  • Outputs DocLang, a compact format built for LLM input and the one we recommend. JSON and plain text are also available.
  • Runs as a single container on CPU hardware, on your own machines or in your own cloud.
  • Two recognition modes: fast mode for high volumes, high-fidelity mode when accuracy matters most.
  • Recognizes more than 200 languages, including Latin, Cyrillic, CJK, and Arabic scripts.
  • Start on the free tier, upgrade to a paid plan as your volume grows, or move to Enterprise for high throughput and offline deployment.