We're not live yet, still tightening things before launch, but wanted to share where things stand.
Inqueria runs real voice interviews, not surveys. This week we ran it against its own research question: what would make someone pay for an AI interview tool, and what would stop them.
A participant said: "The synthesis is what kills me. Two full days, and I've had readouts sit half-finished for three weeks."
Inqueria's next question, generated live: "Tell me about the last specific time you needed evidence from users but ended up running fewer interviews than you wanted, or skipped them entirely."
Dial
you asked for where this breaks, so here's my honest skepticism: the interviewer itself is a variable. two runs of the same study could phrase follow-ups slightly differently and nudge people toward different answers, and that's invisible in the output since you only see themes and quotes, not the exact wording of what was asked. do you log the actual follow-up questions the AI generated per session, so a skeptical reader could check whether the moderator was leading the witness?
@galdayan Fair challenge, and yes. Every question the AI asks, follow-ups included, is saved word for word in the session transcript. Each quote in a theme links back to its session, so you can read the exact question asked right before it. Each session also records which version of the question plan (the plan AI generated based on researcher's objective) it ran against. These transcripts are available to the researcher (the study owner/creator).
The interviewer runs under a hard rule not to lead or suggest answers, but a rule isn't proof, which is why the wording is all kept.
Where you're right: The app provides a client viewing read-only report that the study owner/creator share and they see themes and quotes, not the transcripts, so they'd need the researcher's export to check the moderator. And nothing automatically flags a leading follow-up yet. Showing the question next to every quote is a good idea, and I'm adding it to the list.