App to create animated videos from website/SaaS

Hacker News

I have created a desktop app that can create short and engaging videos for your product/website. You just enter a website and select a template with animations. Or can animate anything on page. Example of how to make a video: https://talevideo.wistia.com/medias/r7qmbljyhx More video examples: https://twitter.com/hey_sergei/status/1469041478437687298 https://twitter.com/hey_sergei/status/1477983425462218753 Key features: - no need to do screen recording - always up-to-date content, you can re-export video with same effect if text on site changed. - select and animate any element on a page - record and replay mouse/keyboard actions. Everyone loves a good video. The problem is that creating a product video can be hard, especially if you’re not a professional. That's why I plan to add much more templates with wizard steps to make nice videos even when you don't know from where to begin. It's still an early beta version and not everything is smooth and has bugs, and not easy as I want it to be. But I really want to hear feedback. What do you think? [Link] https://talevideo.com

Visit product View on Hacker NewsJan 3, 2022

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

91%91% 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 · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

53%53% 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

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

nativeThis product was originally launched on this platform.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

22%22% 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.

Correct prediction on native model

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