Answers · a straight answer, sourced
What is the difference between local, private, and sovereign AI?
Local is about where the computation runs, private is about who can see your data, and sovereign is about who owns and controls the whole stack — three different claims that get sold as one, when in fact a product can be local without being private, private without being sovereign, and sovereign while still honestly admitting parts it does not own.
Local means inference happens on hardware you control. It is a location claim. It rules out the model reading your data on someone else’s servers, but a local app can still leak through telemetry or a cloud fallback — see is running AI locally actually private.
Private means your data is not exposed to parties you did not choose. A product can be private without being local (a well-run hosted service with a real policy) — but then privacy rests on a promise about a system you cannot inspect or leave. Private on a black box is a weaker thing than it sounds.
Sovereign is the strongest and the one most abused. It means you own the layers you can and can exit with everything — the machine, the models, the memory, the data, and a verified way out — with every borrowed layer disclosed. Full sovereignty does not exist for anyone in 2026 (even open weights are someone else’s artifact trained on a corpus nobody outside can audit), so the honest version is maximum control at every layer with the compromises named. That is why SovereignAI publishes a layer-by-layer ledger instead of a checkmark, and defines both the national and personal meanings of the term on what is sovereign AI.
Own the answer, not just read it
SovereignAI is private AI you run yourself: local models, memory with receipts, disclosure at the moment anything leaves, and an exit you can verify. The trial is one Docker command, and deleting the volume deletes every trace of you.