A persona-driven research and testing engine — AI users grounded in real customer research that react to your designs before you ship them.
Real customers, replicated — they think, decide and talk like the segment.
Shown the actual screen, they scroll and tap like a person — never the code.
Reactions weighed against how people actually behave on a phone.
A moderator sets the task, probes without leading, and writes the report.
Main 75–80% save kar leta hoon — parents ke saath rehta hoon, toh kharcha hai hi nahi.
Himanshu · India-3 · the 75% saver on a modest incomeEarns the most, decides the least — agency sits with family.
Collaborative deciders, caregivers, the debt-resigned.
Extreme savers, sharp investors, disengaged spouses.
Outliers kept, not smoothed. Income ≠ agency; savings ≠ income.
Lives with his parents on purpose, banks most of a modest BPO salary, and lets compounding do the rest.
A disciplined saver who defends living at home — the choice that makes the saving possible.
RDs, FDs, digital gold — he tracks what’s invested, not what he might spend.
Compounding is the whole game; he resists one-click EMIs and takes the first option that looks right.
Short, dry Hinglish — trails off, drops a “matlab”, never oversells.
Skims dense English, slides past promos, fumbles small buttons, rarely scrolls far.
12 papers and 5 recorded interviews — every persona decision traces back to a source.
The actual screen, as an image. It scrolls, taps and types like a person — on a phone, by default.
The code, the page structure, the element names. No shortcut to the answer — only what a real user would look at.
Most never scroll past the first screenful.
Dense copy gets glanced at, then skipped.
They grab the first plausible option, not the best.
Anything that looks like an ad is ignored, even if useful.
Crowded, tiny buttons cause fat-finger errors.
Every extra field sheds users; finance forms worst.
Dialled per persona — Mohammed reads the fine print others skim; Danish is pulled by the promo everyone else ignores.
A moderator briefs a real goal on a real flow.
The persona is shown the actual screen, nothing else.
It scrolls, taps and reacts, in character throughout.
The moderator asks neutral, non-leading follow-ups.
Steps out of character and explains its own choices.
Findings written up, weighed against real-user behaviour.
A written report on every run — findings weighed against how real users behave.
Test with your customers before you build for them.
Segment-true reactions to any flow — before you recruit a single participant.
Ask how India-2 reacts to a change and have an answer the same hour.
Every reaction traces to real customer data — and the voices your flows usually miss.