A routable AI compute fabric,
not another single-cluster tool.

mlxMesh federates geographically-spread machines into one distributed inference network — with strict privacy tiers, measured (not declared) performance accounting, and no native token.

Launch Dashboard → GitHub — coming soon

What it is

Most distributed inference tools (e.g. Exo) work within a single LAN cluster. mlxMesh adds a coordination layer above that: it federates multiple clusters across the internet into a routable mesh.

Dual-lane routing

Fast lane for interactive jobs (resolver-routed, low-latency), background lane for recurring/batch jobs (scheduler-routed, sticky-session).

Division-order accounting

Measured resource lines, not declared promises — credits from bootstrap grants decay as earned capacity grows.

Sensitivity tiers

LOW / MODERATE / HIGH_REQUIRES_ATTESTATION, with a Secure Enclave gate on Apple Silicon for the strictest tier.

Ed25519 node identity

Every node's identity is derived from its public key — never operator-chosen, never spoofable.

iOS coordination layer

iPhone/iPad devices classify on-device and host encrypted payload pointers, adding a privacy layer without becoming compute nodes.

Portable wallet identity

An Ed25519 account key, iCloud-Keychain synced and seed-recoverable, that consolidates credits across a user's devices.

Native SwiftUI clients for iOS/iPadOS, tvOS, and watchOS render live topology and drive contribution/coordination directly from Apple hardware.

Open source, AGPL-3.0

mlxMesh is licensed under the GNU Affero General Public License v3.0. Free to use, modify, and distribute under AGPL-3.0 — network users (SaaS) get access to the source, and derivative works stay AGPL-3.0. Commercial use outside those terms (proprietary SaaS, closed-source integration) requires a separate commercial license.

AGPL-3.0 GitHub repo — coming soon