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.

We're Decode by Entropik. Tomorrow we're launching Mira on Product Hunt. But we want to be honest about where AI moderation works vs. where it doesn't.

Where AI wins:

Consistency every participant gets the same quality of follow-up probing

We built Mira to solve a specific problem: AI interviewers that could ask questions, but couldn't read the room.
Traditional qual research is slow. AI tools that came before could moderate but they missed the emotional signal. A participant says "yes" while their face shows confusion. That gap is where insights get lost.
Mira detects emotion in real time via facial coding and voice AI, adapts follow-up questions based on how people actually feel, and delivers synthesis in 48 hours across 70+ languages.
We're launching on Product Hunt on July 7 and would love to hear from the research community:
What's the biggest bottleneck in your current qual research workflow recruiting, moderation, analysis, or something else entirely?
Drop your answer below we read every response and it directly shapes what we build next.