A few people have asked how Mira actually works in practice, so wanted to write this up.
The full flow from start to finish:
1. Set up your study (5 minutes)
Choose a template Customer Discovery, Concept Testing, UX, Brand Perception, NPS follow-up, and more. Or build your own discussion guide. Mira generates contextual follow-up questions automatically, so you do not need to script every question.
2. Recruit participants (built in)
Access 100M+ participants across 120 countries directly from the platform. Set demographic filters, screener questions, and Mira handles recruitment. No third-party panel needed.
3. Run the AI moderated interview
Participants join via link no app download. Mira moderates the conversation, asks follow-up questions intelligently, and reads facial expressions, voice emotion, and eye gaze in real time during the session. Works on a standard webcam.
4. Get your report (minutes, not days)
Automatic transcript with speaker separation. AI themes, tags, summaries, and key quotes extracted automatically. Emotional signal overlaid on each moment. Full research report generated executive summary, findings, evidence, recommendations.
5. Share and store
AI highlight reels for stakeholders no one watches 40-minute recordings. Everything stored in a searchable research repository. Cross-study intelligence lets you compare findings across multiple projects over time.
The part most people ask about:
The emotional layer runs during the interview not after. So when a participant says "I like it" but their face shows hesitation, Mira catches it and probes deeper in the same conversation. That is the core difference from transcript-only tools.
First study is free this month happy to help anyone set one up. Drop a comment below or book here: https://www.entropik.io/book-dem...
See Mira on Product Hunt: https://www.producthunt.com/post...
What type of research are you running? Happy to walk through how Mira would work for your specific use case.
Tried Mira for a quick concept test and the facial coding actually flagged a hesitation I never would have caught in a transcript alone. Slightly surreal watching it react to my own face, but genuinely useful.
Mira
@elanurybrp This is exactly the feedback that matters most, thank you, Elanur.
The hesitation flag mid-interview is one of those moments that traditional transcripts completely lose. You see it in real time, the participant moves on, and by the time you are reviewing notes it is gone.
Would love to hear more about what you were testing, if you want to run a more structured study, first one is free this month. https://aimoderator.entropik.io
Tried Mira for a quick concept test and the facial coding picked up subtle reactions I would have completely missed reading a transcript. The automated report came back faster than I expected and the emotional insights actually felt useful rather than just a novelty.
Mira
@krakl9tl6 "Useful rather than just a novelty" is exactly the bar we hold ourselves to. A lot of emotion AI tools add a layer but do not meaningfully connect it back to the insight. Glad the report turnaround and emotional signals both landed as useful for your concept test.
The facial coding piece is genuinely impressive — caught subtle reactions in a test session I wasn't even expecting to register. Most "AI researcher" tools I have tried just spit out summaries, this one actually digs into how people feel.
Mira
@sleymanpelv3z3 "Summaries vs actually digging into how people feel" is a real distinction. Most tools stop at summarising what was said. The signal that actually drives behaviour lives in a different layer. That is what Mira tries to preserve.
Tried the facial coding on a quick test and the emotion read was scarily accurate to what I was actually feeling during the open ends. The auto-generated themes also saved me a solid hour of tagging.
Mira
@burhanekipepz8 Thank you for putting it through a real test. That gap between what the transcript says and what the face shows is exactly what Mira is built to catch, most tools only ever see the words.
the facial coding piece is wild, didn't think i'd see real emotional response analysis baked into a research tool at this price point
Mira
@serhatmant9b7b Accessibility was a deliberate decision. Emotion AI in research has historically been available only to large enterprise teams with big tooling budgets. Glad that came through.
Onepane
congrats! user interviews are the part of building I always end up skipping because of the effort. this could actually make me do them
Mira
@ashmil_hussain Yes our entire mission behind Decode is to democratise user research. We want all the creators and builders to have data backing their creative decisions and AI guiding them to take better decisions.