01/Overview

Introduction

A unified LLM gateway + knowledge (RAG) platform, run from one admin panel.


The platform is a gateway that unifies many LLM providers behind one API, a RAG system that turns documents into searchable knowledge and MCP servers, and a single admin panel that runs all of it.

#Three pillars

Model Gateway (maestro)

One OpenAI-compatible API. Routes requests to the right model via nodes, model mappings, model groups and advanced flow routing.

Knowledge / RAG (ragify)

Turns documents and datasources into vector knowledge and generates searchable MCP servers.

Admin Panel

The single interface that manages the entire gateway and knowledge stack with live observability.

#The journey of a request

A client (Cursor, Claude, your own app) sends an OpenAI-format request to the gateway. The gateway resolves the model — either a direct model or a model group; if the group uses the "flow" strategy, the request travels through the router graph detailed below to the right member and node.

429/5xx
ClientOpenAI API
routerGatewayresolve model
routerModel Groupstrategy: flow
Member → Nodellm provider
Member → Nodefallback
High-level request flow
Where to start
If you are new, read "Core Concepts" then "Flow Routing" — that is the most powerful part of the platform.