Docling vs Reducto

Docling

RAG

Reducto

RAG

Tagline

Docling

Open-source document parsing for AI: PDFs, Office files, audio and video into clean, structured Markdown/JSON

Reducto

An agentic document platform for AI teams requiring enterprise performance at scale.

Pricing

Docling

Free· Free and open source under MIT License. Hosted by the LF AI & Data Foundation; no paid tiers.

Reducto

Freemium· Standard plan is free with $150 in free usage

Free trial

Docling

Not listed

Reducto

Yes

API

Docling

Yes

Reducto

Yes

Platforms

Docling

—

Reducto

web

Open source

Docling

Yes

Reducto

Not listed

Hacker News stories

Docling

1

checked 2026-10-10

Reducto

8

checked 2026-10-19

Earliest Wayback capture

Docling

—

Reducto

2024-02-21

earliest archived capture of the site, not a launch date

Model used

Docling

GraniteDocling 258M and other vision-language models

Reducto

In-house vision models combined with frontier LLMs (specific vendors undisclosed)

Best for

Docling

ML and platform engineers building RAG systems, doc-QA copilots, or agent pipelines that must ingest heterogeneous documents on their own infrastructure.

Reducto

—

Not for

Docling

Non-technical users who want a point-and-click PDF-to-Word converter, or teams unwilling to self-host and manage a Python service.

Reducto

—

Editorial score

Docling

—

Reducto

—

Use cases

Docling

RAG document ingestionPDF table extractionScientific paper parsingFinancial filing analysis (XBRL, JATS)Enterprise knowledge base preparationDoc-QA chatbotsAgent-based document workflows via MCPOCR for scanned archivesAudio and video transcription for multimodal RAGConverting Office documents to Markdown for LLMs

Reducto

Extracting insights from investor decks, spreadsheets, and SEC filingsExtracting invoice fields, onboarding forms, and financial disclosuresOCR for scanned pages, faxes, and handwritten contentPreparing data for LLM workflows via chunking and embedding optimizationConnecting AI agents via the Model Context Protocol

Pros

Docling

• Broad format coverage: PDF, Office, HTML, EPUB, images, LaTeX, email, plus audio and video
• Genuinely strong PDF parsing: layout, reading order, tables, formulas, and code blocks preserved
• Runs fully local, so sensitive or air-gapped document processing stays on your own infrastructure
• Native integrations with LangChain, LlamaIndex, CrewAI, and Haystack shorten the path to a working RAG pipeline
• Multiple delivery modes: Python library, CLI, HTTP API server, and MCP server for agents
• Purpose-built small VLMs (GraniteDocling 258M) keep GPU/CPU costs modest compared to calling frontier models per page
• Permissive MIT license and Linux Foundation governance make it safe for commercial adoption

Reducto

• Captures complex layouts, tables, and formatting with high accuracy and bounding-box citations.
• Supports PDFs, images, spreadsheets, and slides through a single API.
• Provides multilingual parsing across more than 100 languages, including mixed-language documents.
• Includes intelligent document chunking and embedding optimization for LLM readiness.
• Allows deployment entirely within a customer's own infrastructure for strict security and compliance.

Cons

Docling

• Python-only public library; non-Python stacks must go through the HTTP or MCP server
• High-fidelity parsing of complex PDFs benefits from a GPU, which raises the bar for self-hosting
• No hosted SaaS or managed service: teams must run and maintain their own deployment
• Documentation and examples assume engineering fluency; there is no non-technical UI
• Extraction quality on unusual layouts (multi-column scans, handwriting) still varies and may need post-processing

Reducto

—

Website

Docling

docling-project.github.io

Reducto

reducto.ai

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.