Va

Vaux – The last video and audio editing app you'll ever need

Hacker News

Vaux – The last video and audio editing app you'll ever need

Hey HN, I recently created Vaux:Video and audio editor to end the cycle of having to copy video and audio files to my computer for simple edits. Unlike most video editing mobile apps out there that 'force' you to create a project before editing, Vaux loads up with an interface that let's you pick the action you want to perform, allows a few tweeks then exports the edited file. This is also aimed at the casual editor who just wants to perform a single editing task and move on. The stack: I built Vaux using Flutter and FFMPEG library for the editing tasks. Some of it's features include: -Video FPS Modification -Editing audio metadata -Reversing video and audio -Adding music -Merging, trimming, cutting, muting -Media Speed modification I'm currently working on localization features to support multiple languages and would really appreciate your thoughts and feedback. The app is available for both Android and iOS. Links below: https://play.google.com/store/apps/details?id=com.vaux.vaux_... https://apps.apple.com/us/app/vaux-video-and-audio-editor/id...

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting
92%92% 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: apple, google, apps · Missing: mac, agents, macos
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: mobile apps, ios, apps · Missing: personal, entrepreneurs, month
74%74% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: interface · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, 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
49%49% 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 · Strong signals: audio · 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

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