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Elemo Is Looking for Contributors

Hacker News

Elemo Is Looking for Contributors

Hi HN! I’m building Elemo, an open-source project management platform aimed at helping developers ship faster, giving better visibility, and involving communities in project lifecycles. It’s early-stage: Todo lists are implemented, and I’m working on features like boards, issues, and roadmaps. The goal is to make project management flexible, self-hostable, and community-driven without reinventing the wheel. Looking for contributors to shape the roadmap and implementation!

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Actual performance

2points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: project management, open · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
62%62% 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 · Strong signals: platform, host · Missing: plus, intuitive, reviews
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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