I'm building a website to discover AI tools, AI WITH. ME

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I built this AI navigation site when I was learning NextJS; I looked for AI tools to solve problems along the way, and found a lot of interesting AI products; A lot of these products are great. I thought it would be a good idea to bookmark my browser, but I wanted to share it with everyone in the world, so I had this site. Now you can do it in AI WITH. ME Find the AI products you need for work, life, and study; I have a lot of categories to choose from: programming, art, writing, video, lifestyle, health, you name it, and I try to update the data every day. If you find it helpful to you, you can sponsor me so that I can build this product better. Finally, you are welcome to submit your AI products or tools to the AI WITH. ME", let more people in the world see it. If you want to get access to AI WITH. ME users see your products more often, and you can find the sponsored links I left on the site. Become our sponsor! Thank you very much

Visit product View on Hacker NewsMay 27, 2024

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Actual performance

6points

Did not reach leaderboard

Launch Intel predictions

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

75%75% 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 · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

38%38% 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

15%15% 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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