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title: Offline meeting notes — a local, open-source Otter.ai alternative description: Record a meeting and get a speaker-labelled transcript and minutes entirely on your own machine. No cloud, no account, no per-seat fee, and no bot joining the call. Free and open source.

Offline meeting notes — transcripts and minutes without the cloud

Short answer: if your meetings must not be uploaded anywhere — clinical, legal, HR, pre-publication research, or just internal — YazSes records them on the machine in front of you, writes a speaker-labelled transcript, and can draft minutes with a local LLM. Nothing is uploaded, no account is required, no bot joins the call, and there is no per-seat fee.

This page is deliberately honest about what YazSes does not do. There are good tools in this space; some will fit you better.

The 60-second version

pipx install 'yazses[diarization]'     # speaker labels need this extra (~15 MB of models, fetched once)

yazses meeting start                   # hands-free — no key to hold
# … the meeting happens …
yazses meeting stop                    # → speaker-labelled transcript

You get a transcript like:

Speaker 1: Right, let's start with the migration timeline.
Speaker 2: We're blocked on the staging database until Thursday.
Speaker 1: Then we move the cutover to Monday. I'll tell the customer.

Then, optionally:

yazses meeting relabel <id> --rename speaker_1=Amara         # fix the labels once
yazses meeting enroll  <id> --speaker speaker_1 --name Amara # …or teach it a voice, so it's named next time
yazses meeting notes   <id>                                  # summary, decisions, action items (needs a local LLM)

Everything above runs on CPU. No network access is used at any point.

How it compares

YazSes Otter.ai Fireflies / tl;dv / Granola Meetily, TalkTrack & similar local tools Whisper + your own scripts
Audio leaves your machine Never Yes Yes No No
A bot joins your call No Yes (or app recording) Yes Varies No
Account required No Yes Yes Usually no No
Cost Free, Apache-2.0 Paid per seat — Business is $30/user/month, or $19.99 annual, minimum 5 seats Paid per seat Free Free
Speaker labels Yes (opt-in extra) Yes Yes Usually yes You build it
Minutes / action items Yes (opt-in, local LLM) Yes Yes Often yes You build it
Captures a remote call's other participants Only via the room mic — see below Yes Yes Often yes (system audio) Depends
Also a hold-to-talk dictation tool Yes No No No No
Also transcribes existing recordings Yes (yazses transcribe) Yes Some Some Yes
Install pipx · APT · Snap SaaS SaaS Often Docker n/a

Where YazSes is genuinely different

Local meeting transcription is not a category YazSes invented — Meetily, TalkTrack, and others do it well, and several are excellent if a meeting recorder is all you want.

What is different here is that Meeting Mode is one mode of a general on-device speech daemon, not a separate product:

  • The same install, the same downloaded Whisper model, and the same config also give you hold-to-talk dictation into any app and voice commands for your editor and terminal.
  • The same speaker-embedding machinery powers yazses transcribe <file> for interviews and lectures you recorded elsewhere.
  • No bot, no browser extension, no Docker. It is a daemon you install from pipx, APT, or Snap, and it records the room.
  • Enrolled voiceprints are stored encrypted, on-device only, and are never created without you explicitly asking. Biometric data never leaves the machine.

If you want a meeting recorder and you dictate every day, that consolidation is the argument. If you only ever need meeting notes, a dedicated tool is a reasonable choice.

Where YazSes is the wrong tool

Read this part before you install anything.

  • It records the microphone, not the call. For an in-person meeting — a room, a table, a phone in the middle — this is exactly right, and it is the case Meeting Mode was built for. For a remote call, YazSes hears only what your microphone hears, so remote participants come through your speakers or not at all. If you need clean per-participant audio from Zoom or Teams, use a tool that captures system audio or joins the call.
  • Minutes need a model you supply. yazses meeting notes runs a local GGUF LLM you point it at (the notes extra plus, e.g., a Q4_K_M Phi-4-mini or Qwen2.5-3B). There is no bundled model and no API fallback. Without it you still get the full transcript.
  • Speaker labels are Speaker 1..N until you name them. Diarization finds how many distinct voices there were and groups turns; it does not know who anyone is. You name them once with relabel, or enroll a voiceprint so they are recognised next time. Note that meeting enroll reads the stored recording, so it only works for a meeting captured with [meeting] retain_audio = true — by default the audio is already gone.
  • Accuracy is CPU Whisper accuracy. On a good mic in a quiet room this is strong. In a large echoey room with six people talking over each other, a cloud service with per-channel audio will beat it. That is the trade you are making for privacy.
  • English-tuned by default. It ships *.en models; other languages need a different one.

What actually happens to your audio

Stage Where it lives
During the meeting Streamed to a WAV file in the YazSes data directory on your machine, plus a live.jsonl rolling transcript so a crash does not lose the meeting
At meeting stop Transcribed and diarized locally, then the recording is deleted unless [meeting] retain_audio is on
Afterwards The transcript, and any notes, stay in the meeting folder — plain files you own
Enrolled voiceprints Encrypted in the on-device learning corpus, machine-bound, never transmitted

No telemetry is collected and no network request is made by the meeting pipeline. See the privacy statement.

Recording other people — please read

Consent rules for recording conversations vary by country and, in the US, by state; some jurisdictions require all parties to consent. YazSes gives you the technical ability to record; it does not give you the legal right to. Tell people they are being recorded, and follow the law where you are. Voiceprint enrollment in particular is biometric data — only enroll people who have agreed to it.