I

I made a fun AI tool that can furnish a room in seconds

Hacker News

I made a fun AI tool that can furnish a room in seconds

I'm thrilled to show you PropertifyAi, a tool I whipped up that lets you furnish any space with just a few clicks. Upload your room, pick your style, and bam! Your room's decked out in seconds. Why It's Cool: Fast: From nothing to something in a flash. Fun: Play with styles like a video game. Easy: So simple, even my grandma loves it. Built with some Python magic, a dash of Nuxt, and a lot of late-night pizza. Would love to get your thoughts or hear your wild ideas for features! Check it out and tell me it isn't magic! propertify.ai Cheers!

Visit product View on Hacker NewsApr 25, 2024

Actual performance

2points

2comments

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

55%55% predicted probability of success on Indie Hackers, 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, intuitive

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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