NephoNous — Cloud Mind, A Sovereign AI Solution
Proprietary · A Sovereign AI Solution

A node that never persists patron data cannot disclose it.

NephoNous is a sovereign inference architecture built on owned Apple silicon — sovereignty as a property of the system, not a promise about its operators.

The Film

See the sovereign mind at work

A short film on the architecture, the philosophy, and the case for owning the machine that thinks for you.

NephoNous film poster
NephoNous — Cloud Mind
Film coming soon
The White Paper

A Sovereign Inference Architecture for Apple Silicon

Version 2.0 · by John David Marx · Webspinner LLC — with a fully interactive architecture explorer.

NephoNous white paper
Proprietary & Confidential

Resolving the utilization paradox in GPU datacenter economics

“Sovereignty becomes a property of the system rather than an assertion about its operators.”

The corpus and vector index stay on the patron’s own infrastructure; the inference node receives passages, consumes them within a turn, and retains nothing. Read the full paper — including the interactive Explore the Architecture (DeepDive) — with the scaling arithmetic, the sovereignty case, and every figure attributed to a named source.

Read the White Paper →
The NephoNous sovereign AI architecture
The Architecture

One complete node. Nothing retained.

A federation of individually complete, energy-efficient, unified-memory nodes — each retaining no patron state, coordinated by a gateway that treats prefill avoidance as its principal responsibility. Named in Greek, from Pylon (the gateway) to Katharsis (the guarantee a node keeps nothing).

Explore it interactively →
Why NephoNous

Sovereignty, economics, and a durable moat

I

Sovereignty is a property

The node cannot disclose what it never persists — a stronger compliance posture than encryption at rest, because it depends on the absence of the data.

II

Unit economics invert

Owned capacity turns inference from a metered variable cost into a depreciating fixed asset with negligible marginal cost.

III

Prefill is the moat

The cache tier attacks the cost that dominates retrieval-augmented latency — the one the industry has least attacked on this substrate.