Reflct

Reflct

Product Hunt

The journaling habit you'll actually keep

Most journaling apps give you a blank page and wish you luck. Reflct gives you a mirror. Every evening, answer three guided questions from 120+ rotating prompts. Log your mood in one tap. Then let AI do what humans can't - connect the dots across weeks and months of entries to reveal patterns in your mood, energy, and thoughts you'd never notice alone. Free to start. No credit card required.

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Actual performance

109upvotes
22comments
Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: apps, month · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Strong signals: apps · Missing: mac, agents, macos
47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
26%26% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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