For UX, qualitative & academic researchers

Interview transcription for researchers that passes the IRB.

Quietly runs on your Mac and writes plain Markdown notes to a folder you pick. Nothing uploads to OpenAI, Otter, or anyone else, which is what your consent form already promises.

Download for Mac For your IRB
Free 7-day trial On-device Whisper 99 languages $49 once
What you get
Interview folders, anonymisable.

Plain .md with participant ID, date, and duration in the front-matter. Atlas.ti, Dedoose, and NVivo all read it.

Local · No cloud
P07-2026-04-22.md 58 min · KR
P08-2026-04-23.md 42 min · EN
P09-2026-04-25.md Transcribing
The friction

Cloud transcription tools and IRB protocols don’t mix.

The Whisper API and Otter ship audio off-device. Both send it to OpenAI’s or Otter’s servers, which blocks IRB approval on most studies that touch identifiable speech.

Rev human transcription costs $1.50 a minute. It is accurate, but a 60-minute interview costs $90, and your audio still leaves your laptop.

Self-hosting Whisper costs you a weekend. You end up with half-named files, no metadata, no batching, and no front-matter. Then participant 14 sends an .m4a and the pipeline breaks.

Dovetail and Reduct charge cloud-tier prices to host data your IRB already cleared you to keep local. You pay to add risk.

Why Quietly fits

The boring local-first pipeline you wished existed.

On-device

Audio + transcript stay on your Mac.

Whisper large-v3 transcribes on your Mac, and Quietly deletes the audio file unless you keep it. Nothing leaves the device, which is the sentence your consent form already says.

Markdown

Open in Atlas.ti, Dedoose, or NVivo.

Front-matter has participant ID, date, and duration. The body is clean, LLM-polished Whisper output. Easy to anonymise, import, and cite.

Any audio file

Transcribe existing recordings, no CLI.

Pick Transcribe a file… and choose any common audio or video file (.m4a, .wav, .mp3, .mp4, …). Each becomes a Markdown note. No Python env, no GPU drivers.

99 languages

Korean & English, side by side.

Whisper detects the language per recording. Code-switching interviews (KR + EN) stay coherent, since large-v3 handles them well. We test it daily on Korean academic interviews.

In-person

Lab interviews, fieldwork, intercepts.

Mic-only mode covers in-person sessions. Open Quietly and press ⌘R to start a recording, with no full-screen app and no bot in the room.

$49 once

Doesn’t need a budget line.

One-time license. Cheaper than three hours of Rev. Approve once, use it for the whole dissertation.

For your IRB

The sentence you can paste straight into your protocol.

It reads like the privacy clause your IRB already accepts.

Audio recordings will be transcribed using OpenAI Whisper running locally on the researcher’s device (Quietly, meetquietly.com). No audio or transcript will be transmitted to a third-party server. Recordings will be deleted after transcription; anonymised transcripts will be retained for analysis.

We can provide a one-page technical brief for your IRB. Email support@meetquietly.com.

Your analysis stack

Plain Markdown, so your QDA tools read it.

Atlas.ti
Import as plain text. Quote-level coding works on the transcript paragraphs as they are.
.md / .txt
Dedoose
Upload the Markdown. Dedoose treats each file as a document for thematic coding.
.md
NVivo
Convert front-matter to NVivo classifications with a tiny script. Examples on request.
.docx ←
VS Code · ripgrep
Tag, search, and pull quotes across the whole corpus. It’s plain Markdown.
folder
Pandoc / LaTeX
Convert quotes into your dissertation’s bibliography format with one script.
cli
FAQ

Things researchers ask first.

Is the Whisper model running on my laptop?
Yes. Whisper large-v3 ships inside the app and runs on your Mac's CPU and GPU. Quietly processes the audio file on disk and never sends it over the network. The app only goes online for one-time model downloads, update checks, license validation, and Google Calendar polling if you connect a Google account.
How accurate is local Whisper vs. Rev or human transcription?
On clean recordings (interview-grade mic, quiet room), Whisper large-v3 is comparable to professional human transcription in English and strong in Korean. An on-device LLM cleanup pass then fixes fillers, false starts, and punctuation, so the transcript reads as clean as a cloud service's, with nothing leaving your Mac. Noisy fieldwork audio will need a verification pass, but at $49 instead of $90 an hour, the math still works.
Can I diarize speakers?
Today Quietly splits the transcript into speaker turns, with a new block each time the speaker changes, which works well for two-person interviews. Full per-speaker diarization (labeling each participant, robust enough for focus groups of four or more) is coming soon, along with per-channel diarization for when you record each participant on a separate track.
What happens to the audio file?
By default, Quietly deletes the audio once transcription completes. You can keep it, per recording or always. It stays on your disk in the same folder, with a filename that matches the .md note.
Will my IRB ask for a SOC 2 report?
Some will. Quietly is local-first software, so there is no service to audit. We provide a one-page technical brief that covers data flow, network calls, and where Whisper runs, and most IRBs accept it. For the strict ones, the brief states that audio and transcripts never cross the network, and that the app only goes online for model downloads, update checks, and optional Google Calendar polling.
Can I use this for clinical / IRB-restricted work?
Several research groups use Quietly for IRB-approved interview studies. We don't market Quietly as HIPAA-certified, since that is a service-level claim and Quietly is a local app. The data handling does match what most IRB protocols require: on-device processing, no third-party transmission, and researcher-controlled retention.

Replace your transcription budget with $49.

Free 7-day trial · No account, no card. 7-day refund, macOS 13+. Approve once, use it for the whole dissertation.

$ 49 once · 2 Macs
Download for Mac

Less than 1 hour of human transcription