Launched this week
TinyLottie
Smart Lottie optimization for high-performance SaaS.
25 followers
Smart Lottie optimization for high-performance SaaS.
25 followers
Optimize and compress Lottie (JSON) and dotLottie animations up to 98% instantly. Zero uploads, 100% private in-browser tool for designers and developers.
Mini Course Generator
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@themirproject Love the vibe-coding story - building something useful in a week with AI agents is genuinely impressive. The Global Leaderboard idea is clever too, gamifying performance optimization will definitely drive engagement and give people concrete motivation to optimize.
Mini Course Generator
@osakasaul Thank you so much! It’s great to see that the Vibe Coding journey resonates with you. Building TinyLottie in just a week was an intense but rewarding experiment in how AI agents can accelerate the 'idea-to-product' cycle.
The Global Leaderboard was actually born from the idea that web performance shouldn't just be a chore—it should be a badge of honor. Seeing developers compete to save the most data and climb the ranks has been one of the most exciting parts of this launch.
If you have any Lottie files you've been wanting to shrink, I’d love to see you on the leaderboard! 🚀
Damnnnnn. I'm working on an app called Habit Doom.
I moved away from Lottie animations cause I needed to keep the app size less than 50 MB.
Will give it a try. Is there no quality loss on compression?
Mini Course Generator
@richard_andrews4 That is exactly why I built TinyLottie! Keeping an app under 50 MB is a real challenge when you want rich animations.
To answer your question: No, there is zero quality loss.
TinyLottie doesn't treat Lottie like a video or a raster image; it optimizes the underlying JSON structure. It removes redundant data, simplifies complex vector paths, and cleans up invisible layers that don't contribute to the animation. Your vectors stay crisp, and your animations stay smooth—just with a much lighter footprint.
Give it a spin with your Habit Doom assets. I’d love to see how much space we can save you so you can bring those animations back! ⚡
98% compression on Lottie JSON — is the technique mostly path/coordinate quantization, dropping redundant keyframes, or actually re-encoding to dotLottie's binary format? The answer matters because each of those has a different visual-fidelity trade-off, and "up to 98%" is the kind of number that's true on a specific shape of input.
Mini Course Generator
@sounak_bhattacharya Great question! You’re absolutely right that 'up to 98%' is dependent on the input structure, but here is how we achieve those high-efficiency results without compromising the visual output:
Smart Path & Coordinate Optimization: We apply intelligent quantization and simplify vector paths by removing unnecessary anchor points that don't affect the final shape.
Redundancy Cleanup: TinyLottie scans for hidden or invisible layers and redundant keyframes that often get exported by default but don't contribute to the animation.
JSON Structure Refactoring: Instead of just binary re-encoding (like dotLottie), we focus on refactoring the JSON itself to be as lean as possible while remaining fully compatible with standard Lottie players.
Dynamic Decision Making: The '98%' usually happens on complex, unoptimized exports from design tools where there is a lot of 'meta-data bloat' to clean up.
We aim for the 'sweet spot' where the file size drops dramatically but the curves stay perfectly smooth. I'd love for you to run one of your complex files through TinyLottie and see how the fidelity holds up! ⚡