Aram Huvis is a global leader in skin and scalp analysis technology, providing personalized beauty and healthcare solutions. With a presence in over 70 countries, the company collaborates with leading cosmetics brands to develop cutting-edge diagnostic devices. Their product lineup includes advanced skin and hair analyzers for precise diagnostics, customized skincare solutions based on individual needs, and healthcare innovations utilizing ICT and IoT technologies for comprehensive baby health monitoring.
Skin, Hair and Scalp Analyzers
- The APM PRO is a high-precision skin, hair, and scalp analysis device with AI-powered imaging and real-time assessment, providing detailed insights for dermatologists and beauty professionals.
- The API Analyzer is a lightweight, ergonomic tool designed for efficient skin and scalp analysis, offering a simple interface and reliable imaging technology for precise assessments.
- The ASM Analyzer is a professional tool with a high-definition 5.5″ FHD display, ideal for in-depth skin and hair analysis. It offers advanced analysis functions for skin, hair, and scalp conditions, making it ideal for use in clinics, salons, and beauty centers.
Baby Skincare
Bebescan is a baby health monitoring device by Aram Huvis that uses advanced ICT and IoT technologies to provide comprehensive diagnostics. It assesses body temperature, ear, nose, throat, oral, and skin health using high-quality medical imaging. The device supports Wi-Fi connectivity and is compatible with various platforms, providing parents with real-time, accurate information.
Ceramide Serum and Cream
Atolian ceramide serum and cream are baby skincare products of Aram Huvis with a three-month shelf life, EWG green-grade ingredients, and dual airless containers. They prioritize skin health and require a few attempts for smooth dispensing and proper container closure.
If you are looking for an AI beauty technology device, Aram Huvis offers innovative solutions for your needs.
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View more: AI Beauty Technology for Advanced Skin and Hair Analysis | Aram Huvis
