Speaker turns
When enabled, diarization separates voices but not identities; ambiguous turns still need review.
For researchers, recruiters and journalists
Transcribe interviews with speaker separation
Record the conversation or import a file. AnyBrief keeps a working transcript locally, while your configured LLM can draft analysis using your method.
From transcript to research material
The recording and working transcript remain the sources while an LLM helps organize observations.
Themes and quotes
A prompt can suggest repeated topics and quotations that should be checked against the recording.
Method-specific findings
Needs, barriers, motivations, competencies or editorial angles in your chosen structure.
Different templates for different interviews
Create separate prompts for user research, recruiting interviews and journalistic conversations.
- Audio and video import without changing the original
- Local FluidAudio or whisper.cpp transcription
- Role and name context for the final document
- Transcript and analysis export
Interview transcription questions
Can I use a local LLM?
Yes. Connect Ollama for local text processing. OpenAI-compatible APIs and trusted CLI providers are also supported.
Does diarization know people's names?
It distinguishes voices but does not infer real identities. Add names and roles as context for the final document.
Is AnyBrief built for hundreds of interviews?
AnyBrief focuses on personal work with individual meetings and files. It is not currently a bulk research coding platform.
Keep the conversation, not just an impression
Transcript, audio and analysis in one interview record.