Zynk, Cross-platform, private file transfer that works

Hacker News

Merry Christmas! Your file transfer gift from Santa is here. I built Zynk because I was tired of file transfer being a "solved problem" that still sucked. AirDrop? kinda Apple-only. Cloud drives? Size limits? Waiting for uploads? WeTransfer? caps caps caps. Browser uploads? No folders supported? One network hiccup and you start over. What Zynk does: Transfers files between any devices/OS on your local network, also without Internet connectivity, P2P + E2EE Transfers files between you and anyone else over the Internet, P2P + E2EE Resumable: close your laptop, lose WiFi, switch networks, pick up where you left off End-to-end encrypted (we can't see your files) No size limits, folders, send anything rsync-style, terabytes welcome All platforms supported: Mac, Windows, Linux, iOS, Android, Android TV, Steam Deck UI for everyday use + CLI for power users and automation Web share and drop links for sharing with anyone via browser Media viewer/player built into the app I wanted something that "just worked" the way AirDrop does, but across everything I own and the people I care about. Built-in chat and file previews because context can matter when you're bouncing stuff between people. Even my mom uses it and helps with UX (mom test passed). It's being developed to be a one stop shop tool that is capable of covering any file transfer need and scenario very well. We have a long roadmap ahead. Expect new and unique feature announcements soon. Free, ad free, with Pro tier available for those who need a lot more. Would love feedback from the HN crowd! Happy to answer any questions. https://zynk.it

Visit product View on Hacker NewsDec 23, 2025

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4points

Did not reach leaderboard

Launch Intel predictions

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

88%88% 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.

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

67%67% 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, reviews, soon · Missing: plus, intuitive, host

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

41%41% 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: ios, users, way · Missing: mobile apps, personal, entrepreneurs

38%38% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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