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An AI logo generator that can also generate SVG logos (v2.0)

Hacker News

An AI logo generator that can also generate SVG logos (v2.0)

Back in May this year, I launched CreateLogo, an AI logo generator, which could also generate black-and-white SVG logos. I am now launching CreateLogo 2.0 – completely rebuilt and packed with new models and features such as background removal, vectorization of raster logos and native SVG logo generation. I’d love for you to check it out and share your feedback!

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Actual performance

2points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
64%64% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, models · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, 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
48%48% 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 · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
26%26% 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
13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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