Find out why users hesitate — not just where they click.
Click maps tell you a button got missed. They don't tell you why. Alchemic runs your prototype with an AI moderator that watches every interaction and asks the right follow-up the moment a user hesitates, mis-clicks, or backs out — in their own words, on WhatsApp, web, or phone.
Trusted by brand and insights teams at
Heat maps show what. They don't show why.
Every product team has the same drawer of UX research: a deck of heat maps, a misclick percentage, a 14% drop on the pricing step. You can see the wound. You can't see the cause. So the next sprint is a guess — change the copy, move the CTA, add a tooltip — and three weeks later you re-test and the number barely moves.
The legacy fix is to bolt a UserTesting subscription on top of the click test, schedule moderated sessions, wait a week, and watch eight hours of video. Most teams don't have the budget, the time, or the patience. So the why never gets asked. Decisions get made on instinct, and the same dropoff shows up in the next release.
Alchemic closes the loop in one study.
[ how it works ]
Three things that work together — in one session.
High-fidelity prototypes, not just screenshots.
Import your live Figma file, paste a coded prototype URL, or upload screen flows — Alchemic runs the real interactive thing, not a static image. Users tap, scroll, type, and navigate exactly as they would in the shipped product. Every interaction is captured at the gesture level: which element was touched, in what order, how long they paused, where they reversed course. The fidelity matches the decision you're about to make.
AI moderation that asks why, in the moment.
The AI watches the session live. When a user hovers four seconds on the pricing card, when they tap “Continue” and then immediately back out, when they scroll past the feature they were supposed to read — the AI asks about it right then, in their language, on WhatsApp, web, or phone. Not a generic survey after the fact. A specific question about the specific moment of friction, while the memory is still warm.
A synthesis report, not a data dump.
You don't get a folder of heat maps and 47 video clips. You get a written diagnosis: which screens failed, what users said in their own words about why, which fixes the data points toward, and the verbatims to back every claim. Each finding is cited to the timestamp on the prototype and the respondent who said it. Days, not weeks. Ready to brief design.
[ the process ]
From brief to diagnosis in three steps.
Step 1
Upload your prototype.
Drop in a Figma link, a coded prototype URL, or static screens. Define the tasks you want users to attempt and the questions you want answered. Goes live in under an hour.
Step 2
Users test it; AI moderates live.
Respondents open the prototype on their phone, laptop, or via WhatsApp. They complete the tasks. The AI watches every click and hesitation and asks targeted follow-ups the moment friction appears.
Step 3
Get a diagnosis, not a dashboard.
Within days you get a written report with cited verbatims, click paths, friction points ranked by severity, and concrete recommendations. Every claim links back to the moment in the prototype it came from.
[ why alchemic ]
What makes this different.
Click-tracking AND conversation, in one session.
Maze gives you the click data. UserTesting gives you the conversation. We do both — the AI watches the prototype interaction and asks the qualitative follow-up in the same session, on the same respondent. No second tool, no second study, no second invoice.
The AI asks "why" the moment it matters.
Other AI moderators run a script before or after the prototype test. Ours runs during it. When the user pauses, mis-clicks, or backs out, the question lands while the moment is still fresh — not 20 minutes later when memory has decayed into rationalisation.
Multi-channel reach — your users where they are.
Run the test in-app, on a web link, or over WhatsApp voice. In India and most emerging markets, asking a Tier-2 user to download a desktop screen recorder kills your sample. We meet them on the channel they already use, in the language they actually speak.
Days to insight, not weeks.
Recruitment, fielding, AI moderation, and synthesis all happen on one platform. A 30-respondent prototype study turns around in days. Compare to two weeks of UserTesting scheduling plus a week of analyst time on the back end.