Maxup – A modular ecosystem for youth development using AI

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Hi HN I’ve been developing MAXUP, a modular ecosystem designed to help young people (ages 14–25) grow through structured cycles of training, education, and technical work, all assisted by local AI and smart equipment. The participants (MAX-MANs) are equipped with a wearable kit (suit + helmet) featuring sensors, EMS, and respiratory control, guided by a personal AI assistant (MAXUP-COACH). They operate in teams of 4 (MAXUP-GROUPs), balancing collaboration and healthy competition. The goal is to provide an affordable, scalable and modular system that can be deployed in full-size centers, compact “MAX-ROOMs”, or via personal kits. I’ve also started prototyping an open-source version. Live links: Site: http://maxup.infinityfreeapp.com GitHub: https://github.com/flippe2/MAXUP Whitepaper: summary & full version available in the repo Would love your thoughts — especially around architecture, deployment strategies, or hardware simplification.

Visit product View on Hacker NewsMay 24, 2025

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

77%77% 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: using, open · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, education · Missing: mobile apps, ios, entrepreneurs

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

41%41% predicted probability of success on AppSumo, 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

37%37% 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 · Strong signals: training · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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