Built for researchers · Studies that span months
TigerScribe is the transcription tool researchers can stop fighting. Label a participant once and we’ll keep their name attached across every interview, session, and follow-up — so your codebook stays consistent and your analysis isn’t buried under re-labeling. IRB-friendly retention, no model training on your audio.
Maya
Researcher
How did the new dashboard feel last week?
Daniel
Participant
Honestly? I almost gave up — until the second day.
Priya
Co-researcher
Can you say more about the second day?
Daniel
Things just clicked. The filters made sense.
Maya
What about the export step — did anything trip you up?
Daniel
The CSV worked. The PDF kept losing the header.
Priya
Matches what Sam said in yesterday’s session.
The Speaker 1 problem
Every transcription tool can turn audio into text. Almost none of them keep participants straight when more than three people talk — or remember a voice from one session to the next. That’s the part TigerScribe is built around.
So tell me about your morning routine.
Right, I usually wake up around six and—
Cool, do you—
[unclear] Sorry, that was me.
…the kids by 7:30.
So tell me about your morning routine.
Right, I usually wake up around six and—
Cool, do you—
Sorry, that was me — jump in if I derail.
…the kids by 7:30.
Three pillars
Independent benchmarks put category leaders at 7–10% diarization error rate — climbing past 10% on noisy or 9-speaker audio. We picked the unsexy detail every researcher gets burned by and built the product around it.
01 / Persistent
Train a private voiceprint once. Maya stays Maya across every interview, every co-researcher session, every longitudinal touchpoint — for as long as your study runs.
Your voiceprints are private. We never use them to train models.
02 / Granular
When diarization mislabels a single line, click it and type the right name. The fix is scoped to that utterance — every other line keeps its resolved speaker. Three hours of careful coding don’t evaporate when you re-run the model.
Per-utterance overrides take precedence over the recording-level speaker map.
03 / Default-on
Zero training on your audio, ever. 30-day retention by default with per-recording overrides on the roadmap. Voiceprints stay private to your account. The defaults that pass procurement on first read — not after a six-week DPO conversation.
BAA, SOC 2, and data-export tooling are on the post-launch roadmap.
Built for
We don’t pitch sales teams or Fortune 500 IT — they have Otter and Gong. We build for the researchers whose work falls apart when speaker labels do.
UX / product researchers
Voice IDs persist across longitudinal sessions. Cohort interviews with 5+ speakers stay attributed. Clean exports built for Dovetail, Marvin, and Atlas.ti — without paying $30/seat for two tools just to get a clean transcript in.
Academic researchers
30% .edu discount on Pro. Exports to NVivo, Atlas.ti, and MAXQDA on the post-launch roadmap. IRB-friendly retention defaults out of the box. The pricing tier the rest of the industry forgot to build.
Market & insights teams
Cohort interviews and focus groups stay attributed without manual re-tagging. No per-minute meters running while a long study compiles. Predictable monthly billing your project budget can swallow without an apology.
Clinical & health-services researchers
Built for sensitive interview data: voiceprints stay private to your account, 30-day default retention, never trained on your audio. BAA support is on the post-launch roadmap for Team customers.
Honest comparison
Pulled from public terms, G2 reviews, and the workflows researchers describe in /r/UserExperience and the ResearchOps Slack. Roadmap markers (⏳ M2/M3/M4) stay honest about what’s shipped vs what’s coming. We’ll update this when any of them ships something new.
Dovetail is a research repository / analysis tool that uses an STT vendor under the hood — comparison is on the transcription layer only. Their tagging + theming layer is complementary, not replaced.
Pricing
The market jumps from “free with limits” straight to $17–$30/mo. We added the middle tier the rest of the industry forgot. Verified `.edu` emails get 30% off Pro at signup.
Annual billing saves ~17%
Free
Kick the tires.
Hobby
Grad students and side-of-desk research.
Pro
For full-time researchers.
Team
Research firms · Academic departments · Insights teams.
The anti-bill-shock guarantee.
Hit your monthly minutes? We queue the rest to next month — never an automatic charge. No “overage” line items, no per-minute media meters, no surprise $300 invoices the morning after a long study compiles. If your bill ever changes without you clicking a button, we’ll refund double.
FAQ
Both are solid for live meetings or fast journalism, but they treat speaker labels as a checkbox feature — and reset them on every file. TigerScribe treats persistent speaker identity as the core product. Voice IDs carry across recordings; participants stay named across a 12-week longitudinal study. Plus we never train on your audio.
No. Ever. Your audio is processed, transcribed, and (by default) deleted in 30 days. Voiceprints stay private to your account. Our retention policy and our model-training stance are published on dedicated pages so they can be cited in IRB or legal review.
Today the dashboard renders a fully speaker-attributed transcript you can read and copy from in the browser. Native exports to NVivo (.qdpx), Atlas.ti (.atlproj), MAXQDA, Dovetail-compatible CSV, .docx with speaker labels, and time-coded SRT/VTT for subtitles are on the post-launch roadmap (M3) — we'd rather ship the export pipeline once than ship five half-baked formats.
The default is 30 days. Per-recording retention overrides (24 hours / 7 days / 30 days / 90 days / never) are on the post-launch roadmap (M3) so each study can match its own IRB protocol. Voiceprints derived from a deleted recording are deleted with it. We publish sample IRB language you can lift into your application — ask if you need it before it lands on /trust/research.
BAA support is on the post-launch roadmap for Team customers — once payment processing and the subprocessor BAA chain are in place. Today we default to short retention windows, keep voiceprints private to your account, and never train on your audio. SOC 2 Type II is a planned milestone within the first 12 months.
Any audio or video file the browser will accept — mp3, wav, m4a, mp4, mov, webm, and more — we extract the audio for you. Languages are auto-detected by ElevenLabs Scribe (scribe_v1), which covers 99+ languages including English, Spanish, French, German, Japanese, and Mandarin, with code-switching inside a single recording.
Your transcription queues to the start of next month. No automatic charge. No overage. If you need it now, you can buy a one-time top-up from inside the app — but only if you choose to. The default is always free of surprises.
Design partners · 25 research teams
Free year of Pro for design-partner research teams. We ask for honest feedback in return — and one short testimonial when you’re ready.