I

I build an AI tools for Birthday Invitation

Hacker News

I build an AI tools for Birthday Invitation

I'm Ned, the founder of Birthday Invitation AI. As a parent myself, I know the joy (and stress!) of planning birthday parties. Finding the perfect invitation that matches your child's interests, managing RSVPs from dozens of classmates, and making sure everyone knows the party details—it's a lot to handle on top of everything else. That's why I built Birthday Invitation AI. Our AI understands what you want—whether it's a Peppa Pig party for your 3-year-old or an elegant dinner celebration for your mom's 60th—and creates beautiful, personalized invitations in under a minute. No design skills needed. Just describe what you want in any language, and our AI brings your vision to life. Every invitation includes a QR code that makes RSVPs effortless. Guests scan, confirm, and you see it all in real-time. No more chasing responses or losing track of who's coming. With this Lifetime Deal, you're not just getting a tool—you're getting peace of mind for every birthday celebration in your family's future. Thank you for being part of our journey! Ned Huang Founder, Birthday Invitation AI

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
33%33% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% 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
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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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