A video editor for social media managers

Hacker News

Hi HN, Over the last few months, my team and I have been building a video editor for social media managers, and we just launched it last week. We’ve talked to dozens of professionals, and even though there are tons of video tools out there, the same problems kept coming up: captions that don’t line up, hours wasted cutting silences, managing multiple brands is hard, having to resize content for different platforms takes a lot of time, starting projects from scratch every time, and more. Rendley was built specifically for these people, and we made it our goal to help them create better content, faster. Speaking of features, we’ve got: - An advanced video editor that is easy to use and works directly in your browser - Captions that actually match the timing, so everything aligns with the right moment - A silence remover that cuts all the empty parts - AI integrations for generating videos, images, voiceovers, and avatars. We’ve got popular models, including Nano Banana, Sora 2, Veo 3, Heygen Avatars, and more. There’s also a generous free tier that doesn’t apply any watermark to your videos, so even if you’re editing casually, you can use Rendley without limitations. Would love to hear your feedback and how we can make the product better!

Visit product View on Hacker NewsNov 24, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · 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: model, models · Missing: mac, agents, macos

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

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

65%65% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

Acquire.comPre-revenue stage for this audience · 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

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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