Mira - AI moderated interviews that read how people feel
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Unlike AI tools that stop at interview + transcript, Mira is a full AI researcher — plans studies, recruits globally (100M+ panel, 120 countries), runs dynamic interviews with intelligent probing, and uniquely captures what participants say AND feel via real-time facial coding, voice emotion AI, and webcam eye tracking.
Extracts themes, generates insights, and produces research reports automatically. 17 patents. 70+ languages. Trusted by Unilever, Nestlé and 150+ global brands. $25M Series B.
Replies
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.
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.
Mira
Head of Sales at Decode here.
The conversation I have most with research and insights teams: "Our studies take too long, and leadership does not trust the findings."
Both problems have the same root cause. The tools being used only capture what people say, and analysis is manual. A 20-participant qual study typically takes 6-8 weeks from setup to report, arriving too late to influence the decision it was commissioned to support.
Mira compresses that timeline. Study setup with templates takes minutes. Recruitment from a 100M+ global panel is built in. Transcripts, themes, and reports are generated automatically. Emotional signal adds defensibility to findings.
If you run an insights function and want to understand what this looks like for your team's specific workflow, feel free to ask below.
The facial coding during interviews is genuinely impressive, you can actually see hesitation or excitement that pure transcripts would completely miss. Wish more research tools took emotion seriously like this.
Mira
@mahmutkrc1pj5 Yes, we focus on understanding non verbal cues during interactions and discussions in all of our products. We believe that missing emotion signals might lead to incomplete view of customer's views during interviews and that is why we invested years perfecting multi modal emotion models to provide a comprehensive analysis of customer interviews.
Mira
@mahmutkrc1pj5 Thank you, Mahmut, this is exactly why we built it. The moment before someone chooses their words is often the most honest part of the whole interview. That is the layer that changes decisions.
How does the pricing actually scale for smaller teams or solo researchers who don't need the full enterprise setup, and is there any way to try it before committing?
Mira
@barwcts The best starting point is the free study, no commitment, no credit card. Mention PH when you book: Book a Demo: See Entropik Decode in Action
For pricing beyond that, it scales based on study volume which can be purchased in smaller blocks. Happy to walk through what makes sense for your setup. Drop a note or book a quick call.
the facial coding piece is wild, watching the emotion data overlay during interviews made patterns jump out that a transcript alone would totally miss. really curious how it handles cross-cultural nuance though.
Mira
@burcu192820 Glad the overlay made patterns visible that would have stayed buried in a transcript. On cross-cultural nuance — our models are trained across demographic groups, not on a single population, and we apply normalisation based on cultural benchmarks to reduce bias in emotional scoring. We do not claim perfect universality across cultures — emotion expression varies and it is an ongoing area of work. Our recommendation for global studies is always to combine the emotional signal with the transcript rather than reading either in isolation. The two together are more reliable than either alone.
The facial coding combined with voice emotion analysis during a test interview genuinely caught moments I would have missed in a regular transcript. Feels closer to sitting with a respondent than a typical AI research tool.
Mira
@srammoa "Closer to sitting with a respondent" is one of the best ways I have heard it described. The transcript tells you what they said. Mira tries to preserve what was happening underneath that. Thank you for testing it.
the facial coding detail is wild, never seen a research tool that actually picks up on what people are feeling while answering. ran a quick test on our team and the voice emotion layer caught hesitation I would have totally missed in a normal transcript.
Mira
@nihalzsaki243g The hesitation catch is where the voice layer earns its place; that pause before the polished answer is usually the most honest moment in the whole session. Glad it surfaced. If you want to run a structured study, the first one is free this month. Please feel free to book a demo at https://www.entropik.io/platform/ai-moderator and mention PH20 on the call :)
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 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