AI

AI sticker generator for your loved memories

Hacker News

AI sticker generator for your loved memories

Hello HN, In last 3 months I have been working on a web app where you can create AI stickers for yourself or your business. I have a lovely cat and I wanted to create stickers of her but couldn't find a good solution to do it. I've been working on generative AI and I thought - why I don't create an app for it, a lot of people have pets or memories that they might want a sticker of it. For this reason I have built StickerAIArt. At the moment, you can generate stickers with simple prompts, with reference image of your pet & something you like or with a style of a image. Then if you want you can upscale and remove background to have it ready for physical print with high quality. Also you can automatically receive stickers as WhatsApp message to show your friends. I hope you will find it useful and it can help you to create stickers that you love. Would love to hear your feedback & thoughts Ilker

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: physical · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
49%49% 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
43%43% 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 released
32%32% 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
18%18% 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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