I made a native macOS Twitch client

Hacker News

Kulve is a highly optimized Twitch client built from the ground up for Apple silicon Macs. It features up to 5x the efficiency of the web experience and is fully ingrained into macOS. Main features: - Incredibly lightweight and efficient steam playback using Apple's native video player - Third party emote support (7TV, BTTV, etc) - Support for Twitch's paid services, such as stream subscriptions and Twitch Turbo. - Seamless chatting experience. Kulve's chat UI is handled entirely in-house and designed to be as fluid and ergonomic as possible, utilizing the raw power of M series CPUs to power chats of 100k+ concurrent users. - Battery life. On Kulve, the last thing you will be concerned about is having to find a charger to keep watching your favorite stream. Whether you're focused on the stream or have Kulve running in the background while you're doing other work, Kulve will have 0 impact on your workflow. When Kulve was still in beta, Sourav Dev Sahu took an early look and had great things to say about it. They also left us with some closing thoughts on areas to improve—and we listened! Since then, we’ve launched a complete and total UI redesign with a more focused and polished design language. If you tried Kulve early on, now is a fantastic time to check it out again. Read the full review here: https://techpp.com/2024/10/22/kulve-a-native-twitch-app-for-... and let us know what you think! Another early adopter, the talented Andrew Salfinger from Made by Campfire (www.madebycampfire.com), not only liked the app so much to give us a review, but also went the extra mile to create the official Kulve logo/app icon that you see today. These passionate early adopters are what kept the possibility of App Store launch in scope and we are incredibly thankful for their support over the course of development, all the way from concept to reality.

Visit product View on Hacker NewsMar 19, 2025

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

85%85% 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, macos, apple · Missing: agents, agent, cursor

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: efficient, users · Missing: plus, platform, intuitive

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

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

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

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

19%19% 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, paid · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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