Biscotti is a private and free meeting recorder for macOS. It records your meetings and turns them into accurate, speaker‑labeled transcripts and summaries. No cloud. No bot joining your call. No subscription.
| Biscotti | Other notetaking apps | |
|---|---|---|
| Audio never leaves your Mac | ✅ | ❌ |
| Meeting notes stay private and local | ✅ | ❌ |
| No bot joins your meeting | ✅ | ❌ |
| Works with any app — even in person | ✅ | ❌ |
| Keeps full audio, not just summaries | ✅ | ❌ |
| Native Mac app, not Electron/web | ✅ | ❌ |
| Free, no subscription, no account | ✅ | ❌ |
| Never have to pay to read old meetings | ✅ | ❌ |
| Where your data lives | Your Mac | Their Cloud |
Every step happens on your Mac. Your audio and transcripts never leave your Mac.
Biscotti.dmg.If you use Homebrew, installation is easy:
brew install biscottiIs it really private? Yes. Recording, transcription, and AI all run locally on your Mac. There's no account, and your audio and transcripts are never uploaded. It works completely offline (after downloading models).
Does it join my meeting as a bot? No. Biscotti records your Mac's audio directly, so nothing appears in the call and other participants aren't notified.
What apps does it work with? Anything that plays or records audio — Zoom, Microsoft Teams, Google Meet, FaceTime, Slack, Webex — plus in‑person conversations through your microphone.
Does it cost anything? No. Biscotti is free, with no subscription and no account.
Where is my data stored? Locally, on your Mac.
Which AI does it use? All AI runs locally on your Mac. - Transcription powered by Whisper V3 Turbo, run by WhisperKit - Speaker identification by Pyannote, run by SpeakerKit - Language models by Google Gemma 4, run on llama.cpp
How does it know when to suggest starting/stopping recording? Biscotti monitors active audio apps, without listening to their audio streams. Nothing is recorded unless you click record.
Can I connect my calendars? Yes. Biscotti can sync any calendars you connect to the Apple Calendar app on your Mac. Event data enables meeting start notifications, speaker identity matching, and enhances meeting summaries.
How does speaker idenitification work? Four steps: 1) an AI model transcribes what you say, 2) a second AI model separates speakers by voice + generates voiceprint vectors, 3) we search for voiceprints closely matching these voiceprints in your past meetings which have speaker labels, and 4) a third model figures out who's who balancing evidence (voiceprints, user said "Hi, I'm Steve", etc). Enhanced by calendar metadata when available.
Which languages does it support? The transcription model supports 99 languages and summary model supports 35+ languages.
On‑device speech recognition and speaker identification powered by WhisperKit and SpeakerKit from Argmax.
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