Ranking for 25k AI Tools

Hacker News

Choosing the right AI tool is hard — so we built a public platform that ranks 25,000+ of them with real data. Each tool is ranked monthly using objective data from traffic, reviews, and funding. We publish six independent rankings (overall, traffic, review, investment, risers, fallers) and 150+ category-specific ones (e.g. by industry, use case, or platform). It started as a research project at the Centre for Market Insights (AUAS), and grew into a public platform aimed at decision-makers who want to discover, evaluate, and select the right AI tools with confidence. We’d love your feedback, and we’re curious to hear how developers and builders explore and choose AI tools. Happy to answer any questions!

Visit product View on Hacker NewsMar 27, 2025

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Actual performance

4points

2comments

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · 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.

AppSumoStrong fit for a featured deal · Strong signals: platform, reviews, builder · Missing: plus, intuitive, host

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos

57%57% 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, monthly · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, 000 · Missing: https docs, excited, just released

30%30% 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

12%12% 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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