Create interactive vector animations with Lottielab Interactivity

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I'm excited to announce the release of Lottielab Interactivity, an open standard for defining interactive state machines in files conforming to the popular Lottie format. Along with this standard, we're releasing native support for creating, previewing and sharing such interactive animations in the Lottielab editor, similarly to Rive. We are also releasing Lottielab's Lottie Player, with full support for interactive Lotties and a rich API allowing deep integration in an existing UI. At Lottielab, we've all worked hard on this for months, and we are excited about the possibilities. I've been deeply involved with this work and am happy to answer HN's questions. More about the standard itself, and the accompanying player implementation: https://github.com/lottielab/lottie-player/blob/master/INTER... And some examples: https://lottielab.github.io/lottie-player/playground/

Visit product View on Hacker NewsAug 13, 2024

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Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

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

nativeThis product was originally launched on this platform.

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: mac, activity, open · Missing: agents, macos, agent

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

14%14% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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