Simple File Compressor

Hacker News

A tool to reduce the file size of your files. Free online, local, tracking-free, advert-free file compression. Simple and fast. Now, that the following browser features are implemented by the major vendors: - Resizable ArrayBuffers (since July 2024) - transfer ArrayBuffer to a fixed length (since March 2024) - Compression Streams (since May 2023) nothing stands in the way of selecting a file, compressing it with the CompressionStream API, creating an archive and downloading it. Nothing special per se, but it's another thing, that can now be done using only the browser.

Visit product View on Hacker NewsSep 22, 2024

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Did not reach leaderboard

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

63%63% 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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

25%25% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

17%17% 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

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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