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Glossary

The audio never leaves the machine to become text.

Local transcription means audio becomes text on your own device, not on a server. The recording never has to leave the machine to turn into words.

· 3 min read

On this page (5)
  1. The alternative it's contrasted with
  2. Why it matters beyond speed
  3. What still needs a connection, even locally
  4. How to tell if a tool actually does it
  5. Where it shows up in the category

Local transcription is audio-to-text conversion that runs entirely on the device doing the recording, instead of being sent to a server somewhere else first. The distinction is about where the work happens, not how the result looks: a local transcript and a cloud transcript can read identically, and the only difference a reader can't see is whether the audio that produced it ever left the laptop.

The alternative it's contrasted with

Most meeting notetakers — Otter, Fireflies, Fathom, Granola among them — send the recording to a server for transcription and get text back. That's a cloud architecture: the app on your Mac is mostly a recorder and a client for a service running somewhere else, which is also why those tools stop producing new notes the moment the connection drops. Local transcription is the other design: the software that turns speech into text ships inside the app itself, so there's nothing remote to reach.

Why it matters beyond speed

The practical case for local transcription isn't that it's faster than a server — a fast connection can beat a slow local machine on raw throughput. It's that nothing has to be uploaded for the transcript to exist. A recording that never leaves the Mac can't be intercepted in transit, can't sit on a vendor's servers waiting to be breached, and can't end up training a model belonging to someone else, three separate risks a cloud pipeline carries by design and a local one doesn't have to think about.

What still needs a connection, even locally

Local transcription describes one step, not the whole app. Coii AudioNotes transcribes and writes its summaries entirely on-device, but licence activation still needs the network once, and a launch-time clock check happens on every run. Neither touches the recording itself — the audio, the transcript and the generated minutes never leave the machine — but "local transcription" isn't a claim that the app never talks to a server for anything at all, and a page that implied otherwise would be overselling the one thing that's actually true.

How to tell if a tool actually does it

The giveaway is what happens with the Mac disconnected from the network mid meeting. A tool doing local transcription keeps writing text the whole time; a cloud one stalls, queues the audio, or stops producing anything new until the connection returns. Marketing copy that says "private" or "secure" without saying where the processing happens is usually describing encryption in transit, not local transcription — the two get conflated often enough that it's worth checking the specific claim rather than the adjective around it.

Where it shows up in the category

superwhisper and MacWhisper are the two other Mac apps built around this same idea, each with its own approach to what happens once the text exists. Coii AudioNotes against MacWhisper and against superwhisper cover where the three differ. For the fuller list of what runs on-device across the category, see local transcription apps for Mac and what an AI notetaker does with the text once it exists. Working entirely without a connection, not just for transcription but for the whole session, is covered in offline meeting transcription.

Questions

Does local transcription need an internet connection?
No, once the app is installed. The conversion from audio to text happens using software already on the machine, so it keeps working with the network off.
Is local transcription less accurate than a cloud service?
Not inherently — accuracy depends on the software doing the work, not on where it runs. The trade a cloud service makes for scale is that your audio has to leave your machine first.