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I built a universal clipboard that syncs realtime on multiple devices

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I built a universal clipboard that syncs realtime on multiple devices

I’m Gopal, the guy behind QuickClip. I built this out of pure frustration. Copying items between my phone and laptop was very painful. Sending notes and links on WhatsApp. Saving random drafts I’d forget about. It was total waste of time. So I made QuickClip for myself first. A dead simple way to move text, links and images between devices instantly. No setup drama. No thinking. Fully encrypted I use it every day. Shipping it publicly now to see if anyone else has the same problem. Would honestly love to hear, how you move stuff between devices today, what’s broken or slow and what would make this actually useful for you Happy to answer anything and take suggestions. Thanks for checking it out.

Visit productView on Hacker NewsDec 31, 2025
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: notes · Missing: mac, agents, macos
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% 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
23%23% 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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