Fileloupe for Mac

Hacker News

Fileloupe for Mac

After years of lurking on Hacker News, I figured it was time to finally contribute back. Fileloupe for Mac is a new Mac application that I've been working on for the last year. Version 1.0 was just released in the Mac App Store but Hacker News readers are welcome to download a beta version of 1.1 here: https://kennyc.s3.amazonaws.com/Fileloupe1.1-72-Beta.zip Fileloupe is a high-performance, incredibly fast file viewer that, I think, makes looking at photos, videos, PDFs and documents a lot better than the existing solutions. It doesn't replace Finder (or iPhoto / Lightroom), but rather sits between the two of them in my workflow. If you ever find yourself wanting to browse through the contents of a folder but a Finder window is too restrictive and launching a dozen windows in Preview or Quick Time Player doesn't make sense, then check out Fileloupe. You can find out more information here: http://www.fileloupe.com Things that might be of interest to the Hacker News community: * After working on it for a good chunk of 2014 back in Canada, I moved to Bangkok, Thailand in January to be a "digital nomad" with the goal of finishing 1.0 over here. I rented an apartment, joined a co-working space and met a bunch of other digital nomads working remotely. * It's a Mac application and I'm an indie developer (hopefully), which tends to raise a few eyebrows these days in the world of mobile apps and web based ideas. * I started my career by working in Silicon Valley on Be OS, followed by the first version of OS X and then spending most of my time on the T-Mobile Sidekick (aka: Danger Hiptop). * In 2005/2006 I left Silicon Valley and traveled overland from Barcelona, Spain to Cape Town, South Africa. I'm still trying to find my way home... If you have any questions or feedback, then please let me know. Thank you. Kenny

Visit product View on Hacker NewsJul 6, 2015

Share card

Actual performance

16points

12comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

74%74% 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, apps, new · Missing: agents, macos, agent

69%69% 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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% 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 · 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

Similar products

GIFMaker for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

GIFMaker for Mac

Hacker News1

ShazamScrobbler for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ShazamScrobbler for Mac

Hacker News1

Fastlane – Uber for Mac69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fastlane – Uber for Mac

Hacker News5

Servus for Mac and Dropbox56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Servus for Mac and Dropbox

Hacker News95

Hackernews for Mac65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hackernews for Mac

Hacker News35

Euclid for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Euclid for Mac

Hacker News3

Euclid for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Euclid for Mac

Hacker News2

Buckets for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Buckets for Mac

Hacker News5

Buckets for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Buckets for Mac

Hacker News5

Artful for Mac55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Artful for Mac

Hacker News229

Browse all products Analyze your launch