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BestYou AI - Face rate & Umax

BestYou AI - Face rate & Umax

Younes Oubari

Lifestyle免费v1.0.7
App Store
评分

3.9

35 条评分

星级

★★★★☆

最近更新

2026年4月29日

发布日期

2024年5月14日

更新内容

v1.0.7

Bug fixes and Performance improvement.

应用信息

开发者
Younes Oubari
分类
Lifestyle
价格
免费
版本
1.0.7
App ID
6502551500

简介

BestYou AI is your ultimate companion on the path to becoming the best version of yourself. Our innovative app utilizes advanced AI to analyze your facial features, including jawline, cheekbones, skin quality, and overall harmony. But it's not just about a number. BestYou AI goes beyond a simple attractiveness score. We provide actionable insights and personalized recommendations to help you achieve your goals. Here's what you'll get with BestYou AI: AI-powered attractiveness analysis: Gain a deeper understanding of your facial strengths and areas for improvement. Personalized tips for looksmaxxing: Discover effective skincare routines, hairstyle suggestions, and even mewing exercises to enhance your jawline. (Yes, we cover mewing and mewing exercises!) Confidence-boosting guidance: Feel more self-assured knowing you're taking steps towards your attractiveness goals. A supportive community: Connect with others on their self-improvement journeys within the BestYou AI app. With BestYou AI, you can achieve a healthy hair glow, sculpt a sharper jawline, and find the perfect hairstyle – all with the help of AI and expert advice. Disclaimer: We do not provide medical guidance or advice. All recommendations are to be considered as mere suggestions. We strongly advise consulting with a qualified professional and conducting thorough research prior to undertaking any new actions. *analysis results require subscription. Additional scans require additional purchase. Privacy Policy: https://sites.google.com/view/speechl-privacy-policies/home Terms of use https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

下载量预测

专业 · 预览

预估总下载量

3K2K5K
保守估计乐观估计

73

低 / 月

108

预估 / 月

208

高 / 月

基于35 条评分
假设评分率1.4%
应用年龄24 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。