Local: AI that runs on your machine.
No cloud, no accounts, zero $ per token.

No data leaving your device
Ask questions, draft writing, drop in a PDF and get it summarised.
Point it at a project and it reads, edits and runs code in place. Your codebase is never uploaded.
Transcribed on device, with speakers labelled.
A short list of lasting facts about you, all of it visible and editable. Mark one sensitive and it never leaves the Mac.
Local reads your chip and memory, then recommends what to run.
Tokens, speed per model, and what the same work would have cost through a cloud API.
One device does the work, the office shares it. Run the big model on the most capable machine you own and reach it from Local on every laptop in the room.
Some jobs want a frontier model.
Connect one with your own key, then go back to local for everything else.
Route to a neocloud that keeps inference inside your jurisdiction.
More regions being added
Bring your own key and their top models join the picker beside your local ones.
Local ships BaseRT, our inference engine, compiled for your silicon on first launch. Same model, same Mac, more tokens per second.
We built Local because powerful AI should feel personal, not like renting time on someone else's server.
Yes. You need a connection to download the app and a model. After that, everything runs offline.
Any Mac with Apple silicon. Local picks a model that fits your memory.
No. Everything lives in a database on your Mac. No account, no telemetry.
Yes, with your own API key. Those requests go to the provider, so cloud models are off while privacy mode is on.
Memory decides which models fit, so Local gets more intelligent the better your machine. More unified memory runs larger, smarter models; a faster chip runs them quicker. Local reads both and picks the best setup automatically.
BaseRT, our inference engine. Most local apps ship one generic build. Local installs the one compiled for your chip.