Run private AI on your own device. Own your compute.

Keep prompts and data on‑device. Earn by contributing verifiable edge compute to the CommonCompute network.

Open source Self‑hosted Community‑audited
Early operators get priority access when devices ship and when self‑modded hardware is validated in your region.
Edge device line diagram
Private Edge AI
Why now

Centralized AI is convenient—but not private.

As AI centralizes, your data must never be collateral.

Own Your Compute

Run locally by default. Contribute when idle, on your terms.

Share only what’s needed: proofs of useful work—not your information.

CoCo

Private by default

Prompts and context stay on‑device. No silent uploads. No third‑party training on your data.

Secure coordination

Only signed attestations and anonymized metering signals leave the device. Transparent, verifiable operations.

Simple UX

Plug in, choose models, contribute when idle. Built on open source for auditability and extensibility.

The network

Edge nodes that serve private inference.

Operators earn for verifiable compute and uptime. Governance and accounting are transparent and auditable.

LLM inference at the edge Transparent rewards Open governance Community‑audited
Who it’s for

Privacy‑critical teams

Legal, healthcare, finance. Keep regulated data off the cloud.

Schools & families

Safer defaults. No data exhaust.

Builders & tinkerers

Mod, fine‑tune, and chain local models.

The network

What edge private AI looks like

A constellation of devices—at home, in schools, on the edge—serving private inference without exposing your data.

How it works
1

Get or mod a device

We ship supported nodes—or use our docs to enroll your own hardware.

2

Run private AI locally

Select supported models; keep prompts and data on‑device.

3

Earn for useful compute

Provide inference; earn based on successful, verified work.

Get involved

Join the network

Be an early operator. We’ll notify you when devices ship and when self‑modded hardware is validated in your region.

Built on open source • Transparent protocols and measurements • No black boxes