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Free Online Video Editor Powered by FFmpeg (Runs in the Browser)

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Free Online Video Editor Powered by FFmpeg (Runs in the Browser)

I built a simple, free online video editor that runs entirely in your browser using FFmpeg compiled to WebAssembly. No installs, no uploads, no server load — the processing happens locally, so your videos never leave your machine. Currently supported: • Trim/cut clips • Adjust playback speed • Export locally (MP4) • Privacy-safe (client-side only) It’s surprisingly fast, and works well for: • Social video edits • Quick meme/training clips • Micro-content workflows • When you don’t want to open Premiere/FCP

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
68%68% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released
52%52% 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 HuntUnlikely to reach the leaderboard · Strong signals: mac, using, open · Missing: agents, macos, agent
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
25%25% 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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