Transform Notes into Visual Mind Maps

Hacker News

Hey, HN Community! I'm a Brazilian software engineer, and my educational journey led to a significant discovery. During my master's degree, I often struggled to recall foundational concepts studied years earlier, which were crucial for my current studies. This challenge sparked a reevaluation of traditional note-taking and inspired the creation of cmaps.io. Human thinking is inherently associative, not linear. We often draw connections between learned concepts unconsciously. To leverage this natural process, making these connections explicit is essential – and that's precisely what cmaps.io offers. I can personally vouch for the impact of cmaps.io on my learning and retention. It's become an invaluable tool for me, and I'm confident it can be for you as well! You can find more details on the ProductHunt post: https://www.producthunt.com/posts/cmaps-io Discover cmaps.io and enjoy a revolutionary note-taking experience! I eagerly await your feedback and thoughts

Visit product View on Hacker NewsNov 28, 2023

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

67%67% 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: visual, notes · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · 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.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal, education · Missing: mobile apps, ios, entrepreneurs

41%41% 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

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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