Pullr
Cloud download, hide IP, stream videos & mount WebDAV
What it does
Pullr downloads any link directly to cloud nodes, keeping your real IP completely private. Watch downloads happen in real-time, stream video with subtitles right in your browser, mount storage via WebDAV, or fetch files straight from Telegram. Once ready, grab the archive or share a direct link. No feature gates, you only pay for the storage you use.
Paste a link to fetch—we’ll cloud-download it so sources never see your IP, then watch or grab the zip.
Does the same job
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I’ve always been frustrated with how hard it is to download videos from the internet. Most of the sites that claim to do it are bloated with ads, auto-playing videos, fake download buttons, or just straight-up shady behavior. All I wanted was something minimal that actually worked — no noise, no popups, no tricks. So, I built https://downr.org It's a tiny project that just does one thing: lets you paste a link and download the video. That’s it. No registration, no browser extensions, no messing around with file converters. I didn’t build it to go viral or make money — I built it…
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More work this month
the category →


The app store for voice native apps that lives in your notch
Work · 28d ago · voiceos.com


Mac-native app for screenshots, recordings and collaboration
Work · 5d ago · cleanshot.com
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com