Minforum, modern and minimalistic discussion software

Hacker News

I'm excited to introduce Minforum, a modern and minimalistic discussion software that is open-source and offers a paid subscription model for advanced features. Minforum is designed to be intuitive, customizable, and perfect for communities and businesses of all sizes. Key Features: Open Source: Built with community contributions in mind, Minforum is open source and welcomes developers to contribute and improve the software. Minimalistic Design: A clean and simple interface that focuses on usability and user experience. Customizable: Easily tailor Minforum to fit your community's needs with various themes and plugins. Advanced Moderation Tools: Keep your community safe and engaging with robust moderation features. Seamless Integration: Integrate Minforum with other platforms and services to enhance functionality. Subscription Plans: Access additional features and support with our paid subscription plans. Why Minforum? Minforum aims to provide a straightforward and efficient platform for online discussions. Whether you're a small community or a large enterprise, Minforum offers the tools you need to foster engaging conversations. Get Involved: Try Minforum: Visit minforum.org to explore the features and set up your own forum. Contribute: Check out our GitHub repository and contribute to the project. Feedback: We'd love to hear your thoughts and suggestions! Feel free to share your feedback in the comments. Thank you for checking out Minforum! We look forward to seeing the communities you build with it.

Visit product View on Hacker NewsFeb 15, 2025

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

90%90% 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: model, user, open · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, open source, ide · Missing: https docs, just released, exist

59%59% 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

25%25% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid, introduce · 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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