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Socket.im Get Help Immediatly.

Hacker News

Socket.im Get Help Immediatly.

This was started as a weekend project. And ended up here. Socket,im is a tool for sharing stuff between parties without hassle. You just type socket.im/something then system creates something what we call a socket. You can send links, messages, images etc via socket.im and anyone who is already connected that socket (by also typing the socket name or if you sent him a link by clicking the link) would receive what you have sent. It's anonymous. Nothing is stored on the server persistently. Soon we will add file sharing and ssl support. socket.im is still in its early days so it's something like an alpha version. If you need help from someone immediatly that you don't know him, using internet. Use socket.im ! * New functionalities added. We will be available at http://socket.im/dev

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
61%61% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
30%30% 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
11%11% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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