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ColoringsAI – Custom Coloring Pages from Ideas (My Daughter's Idea)

Hacker News

ColoringsAI – Custom Coloring Pages from Ideas (My Daughter's Idea)

I created ColoringsAI for my 4-year-old daughter, who loves coloring but sometimes gets bored with the same old designs. With this app, you can type in any idea—like “a unicorn in a magical forest” or “a rocket flying through space”—and instantly turn it into a printable coloring page. It’s been a hit in our house, and now I’m sharing it with everyone! Check it out at ColoringsAI and let me know what you think. I’d love to hear your feedback or any fun ideas you come up with!

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Actual performance

53points
32comments
Made the leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting
38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
29%29% 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, 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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