Cork - A digital cork board, demo

Hacker News

Hello HN! Today we'd like to share with you a demo of the web app we've been working on for the past few weeks. We call it Cork. Cork is a digital cork board that you can drop, paste, or type, URLs and text into. After adding an item you can organize it by dragging it around the screen. Our goal is to provide a better way to visualize, organize, and share, content-rich items on the web. We think that current bookmarking system don't do justice to the full spectrum of media online, and we'd like to change that. Please let us know what you think! What do you like? What don't you like? Be harsh if you want to, we can take it. We know that with continued feedback we can make something people love to use. Thanks for your time! http://cork.io

Visit product View on Hacker NewsNov 6, 2012

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4points

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Did not reach leaderboard

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual · Missing: mac, agents, macos

78%78% 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: ide, io · Missing: https docs, excited, just released

69%69% 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 · Strong signals: visualize, way · Missing: mobile apps, ios, personal

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% 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

38%38% predicted probability of success on Indie Hackers, 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 · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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