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.
The facial coding and emotion AI pieces genuinely surprised me, that kind of read on participants usually takes a trained researcher. Watched it pull themes from a test interview in minutes.
Mira
@cal_turkan32795 "That kind of read usually takes a trained researcher" is the most accurate description of what we were trying to automate. The themes in minutes is the time compression — the depth of signal you are working from stays the same.
the facial coding during interviews genuinely caught me off guard, you can actually see the moment a respondent's expression shifts on a tricky question and it ties back to the insight automatically.
Mira
@vedat205337 The "ties back to the insight automatically" is the AI Copilot connecting the emotional moment to the theme it contributed to. You are not just seeing a flag; you are seeing why it mattered in the context of the full study.
Reading how people feel vs what they say is where most user research dies. If the emotion detection is even directionally right, that's a big unlock for solo founders who can't afford research teams.
Mira
@medal411 "Even directionally right" is an honest way to frame it, and that is genuinely where the value sits for a solo founder. You are not running a clinical study. You are trying to know whether the hesitation you sensed in three conversations is real or in your head.
Mira gives you a signal to pressure-test that instinct, faster than you could manually review recordings. First study is free this month if you want to try it on something live.
@productrambler "Pressure-testing your instinct" is exactly the job to be done. Might take you up on that free first study — will reach out.
Tried it on a small concept test and the emotional read from facial coding picked up hesitations I would have totally missed in a regular interview. Insane that it handles recruiting and synthesis in one pass.
Mira
@poyraz853752 The recruiting + synthesis in one pass is one of the things we are most proud of — most tools make you stitch together three or four platforms to get from question to insight. The hesitation catch is exactly where the emotional layer earns its place. That pause before the polished answer is usually the most honest signal in the whole session. Glad it surfaced something useful for your concept test.
The facial coding and emotion layer actually feels different from typical survey tools — I ran a quick concept test and the sentiment data picked up nuances I usually miss in write-ups.
Mira
@gllfevp Thank you for testing it on a real concept. The hesitation read is the whole point. People rarely say "I'm unsure" out loud, but the face shows it, and that gap between what's said and what's felt is exactly what Decode is built to surface
How does the facial coding and eye tracking actually work on participants who don't have webcams or who join from mobile devices?
Mira
@meryemuzuno5kq Right now, you would need camera access to have face emotion measurement or eye gaze tracking done. However, Mira also has the ability to measure emotions purely based on tone of the voice and also based on the words that are being used.
What stands out is the integration of facial coding and voice emotion AI directly into the interview flow rather than bolting them on as an afterthought. That feels like a real research instrument, not just a chat wrapper dressed up with sentiment scores.
Mira
@ayeffrz Ayşe, thank you — "research instrument, not a chat wrapper" is exactly the bar we held ourselves to.
The decision to build the emotion layer into the interview flow rather than running it as a post-processing layer was deliberate. When emotion signals are captured in real time during the conversation, Mira can actually respond to them — adjusting its probing when it detects hesitation or conflict between what someone says and how they react. That closed loop is what makes it feel like a moderator, not a recorder.
The underlying models (facial coding, voice tone, eye tracking) are the same tech we've been building for 9 years across 150+ brand research programs — we just finally wired them into the interview itself.
Would love to show you what a full session looks like end to end → https://www.entropik.io/book-demo