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RAGFreeOpen Source

VANE

Open-source AI answering engine with source citations

MIT

ABOUT

Proprietary AI search engines (Perplexity, Gemini, etc.) require sending queries to third-party servers, raising privacy concerns and offering no customization. Vane solves this with a fully self-hosted answering engine that combines RAG, SearxNG web search, and your choice of LLM — delivering source-cited answers with complete data sovereignty, custom model support, and no usage limits.

INSTALL
docker run -d -p 3000:3000 -v vane-data:/home/vane/data --name vane itzcrazykns1337/vane:latest

INTEGRATION GUIDE

1. Privacy-preserving research: get source-cited answers to complex questions without sending data to third-party AI services 2. Custom RAG deployment: self-host an AI search engine with your choice of LLM, embedding model, and search backend 3. Enterprise knowledge base search: deploy internally to provide AI-powered search over company documents and internal wikis 4. Academic research: use source-cited answering with automatic citation generation for literature reviews 5. Developer documentation search: integrate with local documentation to provide contextual answers about internal APIs and codebases 6. Offline-capable search: run fully offline with local LLMs for air-gapped environments and sensitive applications

TAGS

ragsearch-engineanswering-engineself-hosteddockeropen-sourceperplexicasearxng
Vane — AI Tool | Agentic AI For Good