SplitScreen – Create dual-video content for TikTok, YouTube, Reels

Hacker News

I wanted to share a side-project we’ve been working on: SplitScreen – a tool designed to simplify the creation of side-by-side videos for social media platforms like TikTok, YouTube Shorts, and Instagram Reels. What is SplitScreen? SplitScreen is a straightforward tool that allows you to combine two videos side-by-side in just a few clicks. We built it because we needed a simple, efficient way to create these dual-video posts without the usual hassle. It's made for content creators who want to focus on creativity without getting bogged down in technical details. Key Features: Effortless Merging: Combine two videos side-by-side easily, ideal for reaction videos or other dual-content formats. Intuitive Interface: No complicated steps, just the essentials to get your videos done quickly. Optimized Exports: Fast exports tailored for TikTok, Instagram Reels, and YouTube Shorts. What’s Coming: Custom Split Layouts: Soon, you'll have more control over the layout, with options like 60/40 and 70/30 splits. Direct Uploads: Upload directly from your phone and export content ready for any platform. Speed Enhancements: We’re working on making the process even faster. If you’re interested, check out splitscreen.studio. Looking forward to hearing your thoughts!

Visit product View on Hacker NewsAug 23, 2024

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, intuitive, interface · Missing: plus, reviews, host

70%70% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, way · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

21%21% 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.

Incorrect prediction on native model

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