Self-host Paperless-AI next
v2026.10.02AI document tagging for Paperless-ngx with OCR rescue
- Stars
- 264
- RAM
- ~512 MB
- Port
- 3000 (Web UI)
- Requires
- AI provider (OpenAI, Ollama, Azure, or custom), Paperless-NGX
admonstrator/zettelrobbeWhat is Paperless-AI next?
Zettelrobbe is a fork of Paperless-AI that automatically classifies documents in Paperless-ngx using AI. It connects to a Paperless-ngx instance and uses a chosen AI provider — OpenAI, Ollama, Azure OpenAI, or any OpenAI-compatible endpoint — to analyze new documents and assign tags, correspondents, document types, titles, and custom fields. Key capabilities include an OCR rescue queue that re-processes poorly scanned documents using Mistral OCR or local vision models, a duplicates page that finds and merges similar tags and correspondents with AI assistance, a history page with one-click restore of original metadata, manual tagging for on-demand processing, and a simplify-tags feature to consolidate tag vocabularies. The web UI includes MFA login, OIDC single sign-on support, server-side pagination for large archives, and a guided 7-step installer. It runs as a single Docker image (~500-700 MB) with a bundled SQLite database for history and user accounts, and requires a running Paperless-ngx instance.
Should you self-host Paperless-AI next?
Paperless-AI next scores 49/100 on selfhost.directory (how scoring works) and ranks #31 of 46 in Document Management. It has 264 GitHub stars.
It shipped 21 stable releases in the past year. The latest, v2026.10.02, came out on 22 October 2026. New versions land roughly every 8 days.
Setup is moderate: expect some configuration beyond a single command. An official Docker image is available. It is MIT-licensed and written mostly in JavaScript.
Its closest alternative on selfhost.directory is PaperCortex (35/100, 31 stars). Paperless-AI next scores higher overall. See Paperless-AI next vs PaperCortex side by side.
Features
- Automatic AI document tagging
- Custom fields extraction
- Duplicate detection and merging
- External API enrichment
- Guided installer
- History and one-click restore
- Local AI operation
- Manual tagging
- MFA login
- Multi-Provider AI Support
- OCR rescue queue
- OIDC Single Sign-On
- Rate Limiting
- Server-side pagination and tag caching
- Simplify tags
Paperless-AI next README
FAQ
Does this support a specific niche AI provider?
If it's OpenAI-compatible, it probably works. Otherwise, open an issue and the author may implement it.
Why should I use this instead of the original Paperless-AI?
If the original works for you, stay there. Zettelrobbe offers better performance, improved AI and OCR, and a more polished experience.
What if I find a bug?
The author welcomes pull requests from all contributors and is happy to learn from code reviews.
Why was RAG (semantic search/chat) support removed?
The RAG subsystem required a secondary Python container with ChromaDB, adding massive image sizes, high RAM requirements, and architectural overhead. The project now focuses on core document tagging.
Is this project stable if it's vibe-coded?
The author uses it daily for actual documents and has a strong incentive to keep it stable. Code is reviewed and tested before merging.
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