For qualitative researchers
Analysis starts when transcription ends
Upload an hour of interview audio and get a speaker-labeled, timestamped transcript in under two minutes. Export TXT or DOCX straight into NVivo or MAXQDA, and get on with the part that actually gets cited.
10 free minutes monthly · No credit card
Used by teams worldwide
The transcription bottleneck
Your methods section never mentions the typing
Interview corpora take weeks by hand
Manual transcription runs roughly four hours of typing per audio hour. A corpus of twenty interviews can consume a month of research time before analysis begins.
Human transcription services burn grant budgets
Professional services typically charge between one and two dollars per minute of audio. A single focus-group study can cost thousands of dollars before a single code is applied.
Mislabeled speakers corrupt qualitative coding
When speaker attribution is wrong at the transcript stage, every theme derived from it inherits the error. Discovering the problem at the analysis stage means rebuilding the codebook from scratch.
Verbatim, ready to code
From recorder to codebook in under two minutes
Upload the raw interview file and receive a verbatim transcript with speaker labels and precise timestamps. Every utterance is attributed, so you can code directly from the document without returning to the recording.
- Speaker labels attribute every turn automatically, supporting up to 99% accuracy on clear audio
- Timestamps anchor each passage to the recording for systematic verification
- Export to TXT or DOCX for direct import into NVivo, MAXQDA, or Atlas.ti
“I transcribe patient interviews for qualitative research. Speaker labels are accurate and the timestamps make coding data so much faster.”
Triage before deep reading
Scan an hour of interviews before you sit down with them
AI summaries surface the key passages from each recording so you can prioritize your reading before committing to full analysis. The complete transcript remains searchable for any follow-up.
- AI summary highlights key themes and turning points from each interview
- Full verbatim transcript stays available for deep reading and systematic coding
- SRT and VTT exports available for audio and video recordings with subtitles
Multilingual fieldwork
Fieldwork crosses language lines. Your workflow should too.
Transcribe interviews in 99 or more languages and translate the results without leaving the platform. Speaker labels and timestamps carry through regardless of the source language.
- 99+ languages with speaker attribution and timestamping throughout
- Built-in translation for cross-lingual analysis and reporting
- Accented, code-switched, and conversational speech handled by modern AI models
“Perfect for transcribing lecture recordings. The speaker detection handles multiple professors seamlessly. A must-have for students.”
How it works
Three steps between the field and the codebook
Record Your Session
Use any recording device or software. Upload audio or video files in any format, or paste a URL to a hosted recording.
AI Transcribes with Precision
Our AI identifies speakers, adds timestamps, and handles academic terminology. Technical jargon, proper nouns, and specialized vocabulary are transcribed accurately.
Export for Your Workflow
Download as TXT, SRT, or VTT. Import directly into NVivo, Atlas.ti, MAXQDA, or your preferred qualitative analysis tool.
The descriptive statistics
“It's so fast and the transcripts are incredibly accurate. I use it daily for my research work. The AI summary feature is a game changer.”
The toolkit
Every tool in the lab is free to try
Methods seminar
Questions from the methods seminar
Yes. Our transcripts include timestamps and speaker labels suitable for qualitative research. We recommend verifying key passages against the original audio for peer-reviewed publications.
Yes. Export transcripts as TXT or SRT files that import directly into NVivo, Atlas.ti, MAXQDA, and other qualitative data analysis tools.
Our AI is trained on diverse content including academic lectures and research presentations. Accuracy is highest with clear audio and standard microphone setups.
Yes. Speaker diarization automatically identifies and labels different participants. This works well for focus groups of up to 8-10 distinct speakers.
Our free tier includes 10 minutes of transcription per month. For larger academic needs, contact us about institutional pricing for departments and research groups.
Begin the analysis
Spend the grant on fieldwork, not transcription
Preview 30 minutes of transcription with no signup, then keep a free tier of 10 minutes a month. Join 1,300+ satisfied users who type less and code more.
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