I built ReasonDB after 3 years of fighting RAG pipelines at my company (Brainfish). It's open source and designed to run entirely under your control.

**Why self-hosters might care:**

- **Single binary** — Rust, static build. No Python/Node runtime on the server. Runs in Alpine Docker if you want.
- **One Docker command** — `docker run -p 4444:4444 -e REASONDB_LLM_PROVIDER=openai -e REASONDB_LLM_API_KEY=... ajainvivek/reasondb:latest serve`. That's it. No separate vector DB, no embedding service, no RAG glue.
- **Your data stays local** — Documents and indexes live on your machine. You only call out to the LLM API (OpenAI, Anthropic, Gemini, Cohere, or open models) for reasoning. No sending docs to third-party search APIs.
- **ACID storage** — Built on redb. No external Postgres or Pinecone. Good for homelab or single-server setups.

**What it actually does:**

Instead of chunking everything and vector search, it keeps document structure as a tree (headings → sections → paragraphs) and lets the LLM *navigate* that tree to find answers — like using a table of contents instead of full-text search. So you get precise answers with section references, not "5 similar chunks."

Use cases that fit self-hosting: personal knowledge base, internal docs, contract/policy search, support docs for a small team — anything where you want "ask in plain English, get an answer with a source" without standing up a vector DB + embedding pipeline.

**Query language (RQL):**

SELECT * FROM contracts
SEARCH 'payment terms'
REASON 'What are the late payment penalties?'
LIMIT 5;

Github Link: https://github.com/reasondb/reasondb

ReasonDB – self-hosted AI document database: single binary, one Docker command, no vector DB required