Private, self-hosted meeting AI that runs on your hardware

Most meeting AI is someone else's cloud with a nice front end: a bot joins your call, the audio streams to a vendor, and the transcript, summary, and "who said what" all happen on machines you don't control. Daisy is a private meeting AI built the other way around. The processing happens on your hardware — botless capture, on-device transcription and speaker ID, and AI features through a model you choose. The meeting record is born on the computer in front of you and stays there.

That makes Daisy a self-hosted meeting AI in the only sense that matters for privacy: nothing is processed on a vendor's servers as a precondition of using it. The core loop is local and free, and the single step that can reach the cloud is opt-in and spelled out below.

What "private meeting AI" should mean

The phrase gets used loosely. A tool can call itself private while still uploading every word to a SaaS bucket under its own terms, behind an account it controls. So here's a sharper test: where does the audio get processed, where does the data live, and what has to phone home for the thing to work?

By that test, Daisy keeps the whole core on your machine. Recording, transcription, speaker identification (diarization), and full-text search all run locally, for free, with no account and no sign-up. There's no bot dialing into your call and no telemetry beacon. You install a desktop app and it works on the audio in the room.

Self-hosted, the desktop-app way

Be clear about what "self-hosted" means here, because the word usually implies a Docker image and a box you maintain. Daisy isn't that. It's a local desktop application — self-hosted in the truest sense, in that it runs on the computer you're already sitting at. There's no server to deploy, no container to patch, no reverse proxy to terminate TLS on. You don't operate infrastructure; you run a program.

For the r/selfhosted instinct, that's usually the right trade. The privacy win of self-hosting is "the data never leaves a machine I control." A desktop app delivers that without asking you to babysit a service. The data plane and the control plane are the same laptop.

Where your data lives

Every artifact a meeting produces stays on your disk. By type:

• Raw audio — saved as .wav, plus a compact stereo .opus for keeping. Open formats, your filesystem.
• Transcript — plain markdown. Grep it, back it up, feed it to any tool, or delete it.
• Speaker voiceprints — biometric data, so it's held in an encrypted vault, and it's deletable. This is what lets diarization recognize recurring speakers, and it never leaves the machine.
• API keys — same encrypted vault. No recovery path; they're yours to hold.
• License — one license covers three devices. Activation and the occasional re-check happen online; in between, Daisy keeps working without a connection.

Nothing in that list is locked behind a proprietary blob or a server you don't control. The files are the product, and they're on your hardware.

The one cloud-optional step

Honesty matters here, so: there is exactly one part of Daisy that can reach the internet, and only if you let it. Summaries, Q&A, and analysis need a language model. You pick how that runs:

• A local LLM via Ollama or LM Studio — fully local, nothing leaves the machine. This keeps even the AI features on your own hardware.
• A cloud model you bring (your own key, over HTTPS, no proxy in the middle). The transcript text goes straight to the provider you chose — OpenAI, Anthropic, Groq — under your account, not Daisy's.
• Neither — Daisy hands you the transcript plus a ready-made prompt to paste wherever you like.

That's the honest framing: private by default, your choice to extend. Not "fully private out of the box" — if you opt into a hosted model, transcript text leaves on that one path, because you told it to.

Live captions run on-device too — and they aren't a separate feature that some machines miss out on. Daisy transcribes as people speak and keeps that text when you stop, rather than transcribing your audio a second time; whether the window shows it to you as it arrives is a display toggle in Settings. The cloud never touches transcription in any configuration. Diarization is always on-device and free, in every configuration.

The models are on your machine as well, not streamed from anywhere: the Windows and Linux builds bundle their speech model, macOS 26+ uses Apple's own on-device engine, and Whisper is downloadable when you want another language or the fallback. Every model Daisy fetches is checksum-verified against a pin inside the binary before it runs.

How it compares to cloud meeting tools

Cloud meeting AI — the Otter / Fireflies / Fathom / Granola category — works as a class roughly like this: something captures the call, the audio goes to the vendor's cloud, transcription and speaker labels happen there, and the record lives under the vendor's terms in an account you sign into, usually priced per seat.

The capture end of that is currently in motion. Several of these tools have added a bot-free desktop mode that records your system audio instead of dialling a notetaker into the call, partly because meeting platforms have started flagging and blocking third-party bots. It's a real improvement in etiquette — and it leaves the rest of the architecture exactly where it was. The audio still goes to the vendor.

Daisy inverts each of those choices:

• Processing location — your machine, not a vendor's servers.
• Capture — botless; nothing auto-dials into your meeting.
• Data residence — files on your disk in open formats, no hosted workspace.
• Account — none; no sign-up, no email to start.
• AI model — yours, whether a local LLM or your own cloud key (BYOK, no proxy).
• License — activated online, then good offline between occasional checks.

This isn't a claim that hosted tools mishandle your data — it's a claim about architecture. If your standard is "the recording shouldn't be processed on someone else's servers," the difference is structural, not a setting.

Daisy runs on Linux (AppImage), Windows (.zip or NSIS installer), and macOS (Apple Silicon .dmg). There's a 30-day trial with no account, so you can confirm the local loop on your own hardware before deciding anything.