mvntSTUDIO – AI model that generates dance choreography from music

Hacker News

I think Suno opened up music. Kling and Runway opened up video - but there's one creative domain nobody has touched yet: dance. So my team built an web app — give it a YouTube link to your music and it generates a 3D dance animation in under 2 minutes. The core is a diffusion-based music-to-motion model (mvnt-m4) trained on proprietary mocap/label data from professional choreographers. I think dance is the missing piece of AI-generated content — just like how performance made K-pop a global phenomenon, and we believe AI dance will play the same role in the AI UGC era. This is v0.1 — a fast, experimental playground. Dance quality is still improving (m4.1 in progress), and we're working on faster inference, and finger/facial motion generation. We're also preparing API integrations with platforms like Higgsfield. I think our tech is quite validated through Epic MegaGrant but still very early in finding user validation. Would love honest feedback on the output quality and what you'd want to see next. Also in product hunt: https://www.producthunt.com/products/mvntstudio Demo vid: https://youtu.be/mjq2iAr96iM

Visit product View on Hacker NewsFeb 27, 2026

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

90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% 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

37%37% 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

18%18% 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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