Dequora
Indie HackersDiscover décor items with your unique style.
Making it easy to find the best decoration item that matches your style by crawling the best decoration sites and using ML to find the best fir for you.
Share cardActual performance
2followers
Did not reach leaderboard
Launch Intel predictions
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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal62%62% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released48%48% 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, podcasting22%22% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto21%21% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos19%19% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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