Research transcription at fieldwork scale
Bulk-upload an entire round of interviews. Have them all transcribed, speaker-labelled, ready for coding by the end of the day.
The bottleneck has always been after the interview
Qualitative research only works if you can actually re-read what your participants said. The hard part has never been running the interview — it's the 12 hours of audio sitting in a folder afterwards, blocking the analysis from starting.
Transcrify removes that block. Bulk-upload an entire round of interviews — 30, 50, a hundred — and have them all transcribed, speaker-labelled, ready for coding by the end of the day. Every quote searchable. Every "tell me more about that" answer findable in seconds. Themes that used to require a week of listening are visible in an afternoon of reading.
For agencies running rolling research panels, the same pipeline ingests recordings as they come in and pushes structured transcripts to wherever your team works — Dovetail, Reduct, Notion, a shared drive.
Designed for research teams shipping insights weekly
When fieldwork is continuous, transcription has to keep up — not become the slow part of the cycle.
Multi-participant focus groups
4–6 speaker focus groups handled cleanly with diarization. Larger groups work with light label cleanup.
Moderator vs participant labelling
Researchers automatically separated from participants for cleaner reads and easier coding.
Quote extraction
Search for verbatim quotes across an entire study. Export with timestamps for participant context.
Bulk processing
Drop a folder of 50 interviews. Walk away. Come back to a complete transcribed dataset.
Searchable study archive
Cross-study analysis becomes possible: "What have participants said about onboarding across the last four studies?"
AI-powered theme surfacing
Ask the chat layer to surface common themes, sentiment patterns, or specific topics across uploaded interviews.
From field recordings to first themes
- 1
Wrap fieldwork
End of week, you've got 24 user interviews on the team's recording device.
- 2
Bulk upload
Friday afternoon, drag the whole folder into Transcrify.
- 3
All transcripts ready
By Monday morning, every interview is transcribed, speaker-labelled, and exported into your Dovetail project.
- 4
Start coding immediately
Researchers begin theme tagging on Monday instead of Wednesday. Insights ship a week earlier.
How a round of fieldwork becomes coded data
Bulk upload the recordings
Drag a whole folder of interviews in — 20, 50, 100. Same interface, same workflow.
AI transcribes in parallel
Speaker-labelled transcripts come back, all at once, in minutes per file.
Push into your analysis tool
Direct export to Dovetail, NVivo, Atlas.ti, Reduct or Notion. Coding starts the same day.
Where research teams put it to work
From focus groups to ethnographic fieldwork — wherever a participant's words are the data.
Focus groups
Multi-participant sessions transcribed with clear speaker attribution and verbatim quotes.
User research interviews
UX discovery sessions transcribed and pushed into the team's research repository.
Customer voice
Sales calls and customer interviews transcribed to capture verbatim feedback at scale.
Ethnographic fieldwork
Field recordings, in-context observations and ride-alongs transcribed for thematic analysis.
Survey follow-ups
Qualitative follow-ups to quantitative surveys turned into codeable text.
Competitive intelligence
Recorded competitor webinars, talks and earnings calls transcribed for analysis.
How a UX team shipped insights two weeks faster — every quarter
"We stopped outsourcing transcription a year ago. We ship insights two weeks faster and the budget went into actually paying participants more."
Helena's team runs continuous discovery — about 120 user interviews per quarter, split across web, mobile and B2B segments. They were paying an external transcription service €130 per interview hour with a five-day turnaround.
They piloted Transcrify on one quarter's worth of B2B interviews — about 40 sessions. By the end of the quarter the team had moved everything in-house. The freed budget — about €16k per quarter — went into participant honoraria and longer studies.
The bigger unlock wasn't cost. It was that the analysis phase started on the same day fieldwork ended, instead of a week later. "We were always six insights behind product," Helena said. "Now we're sometimes ahead of them."
Common questions from research teams
Will it identify each focus group participant?
Can I export to Dovetail, Reduct or NVivo?
Does it pick up filler words and interruptions?
Can the AI chat help with thematic analysis?
What about non-English research?
Get the next round of fieldwork analysed in days, not weeks
Try Transcrify on a single interview from your last study. Compare the turnaround to your current pipeline.