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Our Startup Weekend Project

Hacker News

Our Startup Weekend Project

Hey everyone! We would like feedback on our Startup Weekend project, DropSend ( Temporary name ) Here's our pitch: We want to change the way you send files to your friends or contact. Because let's face it,sending a file by email feels really clunky and is limited by the size, Instant Messenger is slow and you need to be online and finally Dropbox while perfect for storing files, doesn't really fit this use case. With our desktop application, one click (and we mean it), is all it takes to send a file. Imagine dragging a file of any size to one edge of your computer screen and see a dock appear with the faces of your friends or colleague. Dropping the file on one of their face will send it to them whether they are online or not. On the other side, your friend, once connected, only needs to accept your request on his computer ( X-Platform client) for the transfers to begin. The transfer is fully encrypted and if your friend is on the same local network, there is no need for an internet connection. When offline, the file is temporary stored on our servers. Monetization would be achieved with monthly bandwidth quotas on files sent through the web. The cross platform client is nearly ready. ( should be really usable in the next few hours ) and we are trying some UI ideas. We set up a landing page for now so you can check it out at http://www.dropsendapp.com If you like the idea, just click download you won't download anything for now, but it will count as "vote" for our market validation. Cheers!

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Actual performance

22points
20comments
Made the leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% 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: ide, io · Missing: https docs, excited, just released
64%64% 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: computer, dock, email · Missing: mac, agents, macos
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, monthly, way · 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
10%10% 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
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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