Kozhya Disrupts the Skincare Industry with AI-assisted Product Development

Kozhya aimed to reinvent skincare with AI-assisted medicinal skincare development and a recommender system.

Partner Overview

KOZHYA aims to disrupt this industry with AI-assisted medicinal skincare development and a recommender system alongside an alternative serum delivery device. 

KOZHYA’s mission is to enhance the efficacy of active ingredients in skincare. As serums with a high concentration of active ingredients have become a must-have step in modern skincare routines, the key question for KOZHYA is how potent and powerful are the active ingredients and how deep do they go into the skin?

With an aim to revolutionize the world of skincare, KOZHYA has introduced the world’s first new portable skincare atomiser, KOZHYA Air, that uses pressure-based technology to break active ingredients, and the specially developed KOZHYA Active Serum, into micro-particles for better skin absorption. 

Business Challenges 

Individual skin treatment plan development requires multiple visits to the dermatologist. It is costly for a patient from both a financial and timing perspective.

The R&D process that delivers medicinal skincare is associated with expensive failures. Usually, it requires a significant lab and human resources to create a new serum. Many candidates are weeded out in the process due to instability, insolubility, or incompatibility of components. 

Solution 

To ensure remote assessment of a patient’s skin condition, we use algorithms powered by artificial intelligence from a patient’s face image.

This automated test is later automatically combined and aligned with the questionnaire results. As a result, a personal skincare program is created interactively, without a need to visit a dermatologist, using AWS Sagemaker. 

Innovative serums are created qualitatively and quantitatively by machine learning technology. This way, the choice of prospective components is narrowed and incompatible combinations are excluded prior to the experimental phase, using AWS Sagemaker. 

The landing zone establishes a secure, scalable foundation for AWS. The landing zone includes AWS Control Tower, AWS Security Hub, AWS CloudTrail, AWS Config, AWS GuardDuty, AWS VPC, AWS Service Catalog, and other AWS services 

MLOps pipelines ensure the easy building, training, and deployment processes for AI/ML models. The solution includes AWS SageMaker Pipelines, AWS SageMaker Training, and Inferences, AWSCodePipeline, AWS CodeBuild, and more. 

Self-service portal provisions infrastructure patterns with AWS Service Catalog. The portfolio includes MLOps pipelines, VPC products, and AWS Account Factory.

AWS Cloud Foundation

Implementation Diagram

Results 

Before 

• Time-consuming and costly personal skincare plan creation
• Serum development processes with a high degree of risk 

After

• Fast, interactive and fully digital personal skincare plan development from home
• Serum composition is predicted via machine learning, reducing the risks of laboratory failures by 63%