Introducing Debriefer
AI-powered qualitative research interviews, designed for speed and depth.
By Debriefer Team
We built Debriefer because qualitative research is too slow.
Conducting interviews manually means weeks of scheduling, transcribing, and synthesising. Teams skip it entirely or settle for shallow surveys. The insights that come from real conversations — the kind that change product direction — get left on the table.
What Debriefer does
Debriefer runs AI-powered interviews on your behalf. You design the script, define the goals, and Debriefer handles the rest:
- Adaptive follow-ups — the AI probes deeper based on participant responses
- Runs at scale — interview hundreds of participants simultaneously
- Structured output — responses are organised and ready for analysis
How it works
- Design a script with your research questions and interview goals
- Share the interview link with participants
- Review structured responses as they come in
Each interview adapts in real time. If a participant mentions something interesting, the AI follows up — just like a skilled researcher would.
Built for developers
Everything in Debriefer is API-first. You can create interviews, manage scripts, and retrieve responses programmatically. We also support MCP integration for teams using AI-native workflows.
Check out the API Guide and MCP Guide to get started.
What's next
We're in invite-only beta right now. If you're interested in running AI-powered interviews for your team, get in touch.