What "local-first AI" actually means, and why it's harder to fake than it sounds

"Local-first" gets used loosely in AI marketing right now — sometimes it means "we cache a bit on your phone," sometimes it means nothing verifiable at all. We use it in a narrow, specific sense for B.A.I.S.: the assistant's core conversation, memory, and command handling run on a model on the device itself, over a local connection, with no round trip to a cloud API required for it to work.

Why that's a real engineering constraint, not a slogan

Building a genuinely local assistant is more restrictive than building a cloud one. You give up the biggest, newest hosted models. You have to fit reasoning, memory recall, and command parsing into whatever compute is actually sitting in the room. It's a harder problem, on purpose — because the alternative (calling out to a cloud API and calling it "local" anyway) is the thing that makes the term meaningless in the first place.

How we check it, rather than just say it

The test we actually run: disconnect the machine from any network at all — no loopback tricks, no local proxy standing in for the internet — and confirm the assistant still holds a conversation, recalls something it was told earlier, and responds to its command set. If it can't do that with the cable out, it isn't local-first, whatever the pitch deck says.

That's the same standard we hold ourselves to when we talk to a partner or an investor: a claim gets made only after it's been run, not because it sounds right in a sentence.

Why it matters to a buyer, not just an engineer

For a household product, this is a privacy answer: a conversation in your home doesn't have to leave the building to be useful. For an assistive-tech or care-sector partner, it's frequently a procurement requirement, not a preference — see our note on the UK telecare analogue switch-off for why that distinction is about to matter to a lot of buyers at once.

Want to see it run with no network route available? Get in touch — that demo takes fifteen minutes.