About Ragmux
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Ragmux is a self-hosted AI gateway. It sits between your applications and the model providers you use, exposes a single OpenAI-compatible API, and can add retrieval from your own documents to every request it forwards.
Why it exists
Most teams reach the same three problems at once: provider keys spread across services, no honest answer to “who spent what, on which project”, and a retrieval stack that arrives as a second database to operate.
Ragmux answers all three in one place. Provider credentials stay server-side and encrypted. Each project gets its own key, its own model connection, its own system prompt and its own budget. Documents, chunks and vectors live in the same PostgreSQL database as everything else — so what you back up is one database and one secret.
What it is, concretely
- A single Go binary, statically linked. The gateway-only
-appimage is distroless; the default all-in-one image is built onpgvector/pgvector:pg17. - One container by default: the gateway and its own PostgreSQL 17 with pgvector, with a split layout and a separate database available. No Redis, no separate vector database.
- An OpenAI-compatible
/v1surface, JSON and SSE, that the official SDKs speak by changing two lines. - Adapters for OpenAI, Anthropic, Gemini, DeepSeek, Ollama, and anything OpenAI-compatible you run yourself.
Who builds it
Ragmux is developed in the open under the Tunedness umbrella. The source, the issue tracker and the documentation are all in the project repository.
It is still being built. The changelog is the honest record of what works today, and the roadmap section on the home page lists what is deliberately not in the current release.
Licence
Ragmux is free software licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later). The AGPL’s network-service clause applies: if you run a modified version as a service that users interact with over a network, you must offer those users the corresponding source of your modified version.
This website’s terms are separate from the software’s licence — see Terms of Use.
About Tunedness
Tunedness is an applied AI research and engineering lab under the Centvix umbrella. It tunes frontier models into systems that teams can operate in production. The products and projects under Tunedness are built on the same research, to Centvix’s shared standards with Tunedness’s own standards layered on top. Each one is designed to be measured before it is trusted and to stay maintainable after it ships.
About the founder
Muhammet Şafak is the founder of Centvix: a software engineer, systems architect and engineering researcher who has been building software since 2008. The current focus is the architecture, scalability and reliability of high-traffic distributed systems. That work includes independent research examining system behavior through reproducible measurements, always choosing technology by the problem rather than the language. The rest of the time goes into open-source tools and infrastructure software under the Centvix umbrella.