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Introducing Respan Router

Docling vs WhyHow (2026)

Updated April 29, 2026

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Overview

Rating
10.0 / 10
Rating
10.0 / 10
Best For
RAG and AI engineering teams that need accurate, structured ingest of PDFs, DOCX, and complex documents into LLM pipelines
Best For
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Product Summary

Docling is IBM's open-source document conversion toolkit (Apache 2.0) that turns PDFs, DOCX, PPTX, and other formats into structured JSON or markdown using advanced layout analysis and table structure recognition. Now ships with Granite-Docling-258M — IBM's compact vision-language model purpose-built for accurate document conversion — and was donated to the Linux Foundation's Agentic AI Foundation in 2026.

Product Summary

WhyHow provides tools for building and querying knowledge graphs from unstructured text using LLMs.

Starting Price
$0Per forever
Starting Price
—
Free Trial
Yes
Free Trial
No
Free Version
Yes
Free Version
No
Website
Website

Key features

Core capabilities each platform advertises.

DoclingDocling
  • Converts PDFs, DOCX, PPTX, HTML, images to structured JSON/markdown
  • Granite-Docling-258M VLM model purpose-built for document understanding
  • DocTags markup preserves layout, tables, equations, code blocks
  • Apache 2.0 — fully open-source and self-hostable
  • Production deployment via Docling OpenShift Operator (Red Hat)
WhyHowWhyHow
Data not available

Strengths and tradeoffs

What each tool does well, and the limitations to keep in mind.

DoclingDocling

Pros

  • Purpose-built VLM beats general-purpose OCR on complex layouts
  • Apache 2.0 license — fully open and self-hostable
  • IBM-grade engineering with Linux Foundation governance
  • DocTags standardized markup makes output portable across tools
  • Production deployment story via Red Hat / OpenShift

Cons

  • Setup complexity higher than hosted document APIs
  • Granite-Docling-258M still requires GPU for fast inference
  • Less polished UX than cloud DocAI services from Google/AWS
  • Smaller ecosystem than Unstructured.io for non-IBM stacks
WhyHowWhyHow

Pros

  • Specialized focus on knowledge graphs for RAG optimization
  • Open-source approach with community-driven development
  • Native integration with vector databases for seamless Graph RAG
  • Supports multiple file formats including PDF, CSV, JSON, and TXT
  • Small, focused team able to move quickly and iterate

Cons

  • Very limited public information about pricing and product details
  • Small team (9 employees) may limit support and feature development
  • Relatively new company (founded 2024) with less proven track record
  • SDK and some features still in development
  • Limited enterprise adoption evidence

What people are saying

DoclingDocling
IBM Research blogresearch.ibm.com

Granite-Docling-258M is purpose-built for accurate and efficient document conversion, unlike most VLM-based approaches that adapt large general-purpose models.

Read full review
WhyHowWhyHow
Data not available

Docling or WhyHow — which should you choose?

Choose Docling if you want

  • RAG ingest pipelines that need clean structured text
  • Financial and legal document parsing (banking)
  • Scientific paper ingestion preserving equations and tables
  • Enterprise knowledge base ingestion at scale
  • On-prem document conversion for regulated environments

Choose WhyHow if you want

Data not available

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