Terminology · Sovereign AI
Sovereign AI
The organisation using an AI system keeps control of the data, models and compute it depends on, within its own jurisdiction and infrastructure.
Definition
Sovereign AI is a question about who holds control. Using IDC's common three-layer split: data sovereignty — production data stays where it is produced; model sovereignty — the user has an arrangement over the models it depends on; compute sovereignty — the compute behind inference and training is not subject to outside factors beyond the user's control.
In manufacturing this is not a compliance option but a precondition. Yield curves, defect libraries and process parameters are crown jewels; if a solution only works once those are uploaded, it is out before the pilot starts.
How it differs
| Layer | The question it asks | DaoAI's position |
|---|---|---|
| Data sovereignty | Does production data ever leave the site | 100% on-premise deployment; sample images and inspection data never leave the plant |
| Model sovereignty | Does the user have an arrangement over the models | Delivered as a private installation; specifics are agreed per project |
| Compute sovereignty | Where does inference run | At the edge of the line; a network outage does not stop inspection |
Why this was in the design from day one
DaoAI is positioned as a leading enterprise in sovereign physical AI. The general route assumes data flows to the model; in industries that treat yield curves as crown jewels, that assumption does not hold.
The DaoAI World platform —— the end-to-end chain and deployment
ACI equipment and software —— what it looks like on the line
Privacy policy —— our public statement on data handling
About DaoAI —— company positioning