I built multi-language search engines for 200k icons and 5k emojis

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OpenAI created a gold mine, and over the past year developers worldwide have flocked to it. I also joined the gold rush and successfully uncovered two gold nuggets of my own: Yesicon (https://yesicon.app): A vector icon search engine supporting 8 languages with over 200,000 high-quality icons, the ⌘CV buddy for developers and designers SearchEmoji (https://searchemoji.app): An emoji search engine supporting 30 languages, enriching articles and social texts with colorful emojis As a front-end developer, I use many icons in my daily work. Iconify largely solved my icon needs but still had one pain point – as a non-native English speaker I often needed translation software when searching for icons. When OpenAI released their API, my first thought was: I will use it to build a multi-language icon search engine. That’s how Yesicon was born. As I could only work on it in my spare time, it took nearly half a year before I could launch it. To my delight, the response after launch was fantastic. Influencers on social media continuously helped promote it. Currently it already has 121k visitors per month, with users from all over the world. In some ways, I succeeded! I feel like I’ve discovered the secret formula for traffic – if you have the resources, you can leverage AI to deliver those resources to users worldwide, and GPT-3.5 alone enables this. But lacking substantial resources myself, I could only set my sights on free resources. Iconify was like this, and so were emojis. I built the emoji search engine to scratch my own itch. Finding the emoji I want when writing documents is a pain. SearchEmoji just recently launched – I welcome you to try it out! Any feedback would be hugely appreciated. SearchEmoji’s code is open source and can be accessed via the Github link in the top right corner of the website. Of course, I sincerely hope you will also try out Yesicon and give me some feedback. If you are a designer or front-end developer, you will find it indispensable. I am also currently thinking about how to monetize the traffic, so I would love to hear your suggestions as well.

Visit product View on Hacker NewsDec 18, 2023

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

95%95% 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: user, openai, code · Missing: mac, agents, macos

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, 000 · Missing: https docs, excited, just released

61%61% 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: month, users, way · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

43%43% 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

22%22% 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.

Incorrect prediction on native model

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