RAGFlow
Deep document understanding — the one for messy PDFs and real-world files.
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sovereigntyRAGFlow's differentiator is what happens before retrieval. Most RAG failures are not retrieval failures at all — they are parsing failures, where a table became word soup or a two-column layout interleaved into nonsense during ingestion. RAGFlow puts layout-aware document understanding at the front of the pipeline, handling tables, figures and multi-column layouts, and it shows you the chunks so you can see what the model will actually be given. Apache-2.0, ships with a web UI.
OPEN SOURCEApache-2.0SELF-HOSTLOCAL-FIRST
LicenseApache-2.0
PricingFree to self-host, Apache-2.0. A managed cloud tier is offered separately.
Open sourceYes
Self-hostableYes
Local-first dataYes
What it does well
- +Best-in-group parsing of tables, figures and complex layouts
- +Visible chunks — you can see and correct what was extracted
- +Full application with a UI, not just a library
- +Apache-2.0
Where it falls short
- −Heavier to deploy than a library (Docker Compose stack)
- −Opinionated pipeline — less swappable than LlamaIndex
- −Document parsing is compute-hungry on large corpora
RAGFlow as an alternative to
Where RAGFlow shows up in our comparisons, and how it ranked.
RAGFlow head-to-head
Straight comparisons against the tools people weigh it against.