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Welcome

The Sirens promise convenience. The giants own the gates. The sea is faster if you let someone else steer. OdyssAI is for those who would rather take the helm.

OdyssAI builds CoeOS: frontier-grade AI at open-source prices, where confidential work stays where you decided. Underneath sits OdyssAI-X, our own inference engine for Apple Silicon, for everything that runs on your premises.

This page tells you what the pieces are and which one you need.

PieceWhat it is
CoeOSThe product. A client, where you work, and the CoeOS box, the router that sends each request to the model proven best at that skill. Two ways to work: the web app, and CoeOS Desktop, the agentic harness on your machine (macOS, Windows, Linux). Run for you as a managed service, one dedicated instance per client.
OdyssAI-XThe engine. Distributed MLX inference on Apple Silicon: single node, multi-node over RDMA (Thunderbolt 5, 120 Gb/s), and replica mode with continuous batching. OpenAI- and Anthropic-compatible API. It serves the Hybrid and Local levels of CoeOS.
TMBThe benchmark of The Monocle Bear: 42 tests, 17 axes, every model scored axis by axis. The routing tables of CoeOS come from it.
CoeOS web app · CoeOS Desktop
↓
the CoeOS box one address, one axis per request, one class per request
↓
cloud providers · OdyssAI-X on your Apple Silicon
OpenHybridLocal
Confidential goesyour choice: no distinction, or EU providers under DPA + ZDRto a model hosted on your premisesstays on site
The rest goesto the cloud, best model per axisto the cloud, best model per axisstays on site

Everything is a setting: providers, contracts, what runs at home. Details: What CoeOS is.

You wantReach forRead
A team AI at a fraction of the price of closed models, with confidential work kept where you decideCoeOS, as a managed instanceWhat CoeOS is
An agent with full access to your machine, routed by CoeOSCoeOS DesktopCoeOS Desktop
Frontier open-weight models served on your own MacsOdyssAI-XInstall the engine

Using CoeOS day to day (first steps, agents, confidentiality, memory) is documented on docs.coeos.io. This guide covers how the pieces fit together, the engine, and the benchmark.