SlikSafe – A decentralized, end-to-end encrypted alternative to Dropbox

Hacker News

Hey folks, We are the team behind Slik. Over the past year, we have been hacking on SlikSafe [1] a Dropbox alternative where all your data is first encrypted on your own device and then stored on decentralized storage. Some features we're most excited about are - - multi-device data sync, - auto-backups via desktop apps, - search your docs by name or contents with end-to-end encryption, - easy sharing via email, QR-code or private-link, - Password-less login using MetaMask/Phantom We leverage storage providers IPFS and Storj for global redundancy, reliability, and immutability. You can use our web app [2] and macOS app [3] today. Our desktop app for Windows is currently in beta, and will be launched in early Jan. You can read our WhitePaper [4] for the technical implementation, or see a quick demo [5] of the product. Would love to hear what you think. Arpit, Charvi [1] SlikSafe: https://www.sliksafe.com [2] Web app: https://app.sliksafe.com [3] macOS app: https://sliksafe.com/downloads [4] WhitePaper: https://sliksafe.com/whitepaper.pdf [5] Demo video: https://www.loom.com/share/abe133c4ce874655a952a30601e99408

Visit product View on Hacker NewsDec 21, 2021

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Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

87%87% 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: mac, macos, apps · Missing: agents, agent, cursor

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, video · Missing: mobile apps, ios, personal

37%37% 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

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

21%21% 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.

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