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Introwise – All-in-one platform for events and communities

Hacker News

Introwise – All-in-one platform for events and communities

Hello HN! We at Introwise just released a major addition to our product - Communities. In a nutshell - it's a combo of Slack/FB Group/Meetup. We wanted to create a product where community members are encouraged to contribute and share - we do that through group chats based on common interests with smart recommendations, and through a community-driven calendar where anyone can add their meetup. Communities can also host public-facing events, allowing them to grow. Here is the playground, an example community: https://introwise.com/communities/introwise You'll have to sign up, but you can always leave/remove your account hassle-free. It's a very early announcement here, so even our homepage and marketing pages are still in development. I'm particularly interested in what HN members think about our product. Many communities we are targeting - co-workings, incubators, coding schools, are very tech-heavy and mostly rely on Slack. But at the same time we've heard a lot from them about problems of running their communities on Slack - can become noisy, intimidating for newcomers, complicated for non-tech-folks, expensive. What tools are your communities using? I'm a co-founder and the only developer, so ask me anything! The web app is SPA React backed by Firebase, event-driven server-less architecture.

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% 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: slack, new, using · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: just released, io · Missing: https docs, excited, exist
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, smart · Missing: web3, crypto, cryptocurrency
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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