AI/AR Skin Analysis
ulta beauty

About This Project‍

In 2019, I contributed to a groundbreaking initiative at Ulta Beauty, focusing on the development of an AR and AI-powered Skin Analysis service within the Ulta Beauty App for both Android and iOS platforms. This innovative project, aimed at enhancing the skincare shopping experience, allowed users to undergo a smart, in-depth analysis of their skin by simply answering a few questions and allowing access to their camera feed. The integration of AR and AI technologies provided guests with a virtual, customized skin report diagnosing conditions such as redness, breakouts, dark spots, and fine lines.
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As the main developer for a backend service that was used as a middleware, my role was crucial in building the service's infrastructure in Node.js, integrating APIs that provided access to proprietary computer vision technology as well as external API's for product recommendation, and then deploying our solution on Google Cloud. This ensured scalability and reliability, allowing Ulta Beauty to offer intelligent, personalized skincare recommendations and product selections tailored to each guest's unique conditions and skincare goals.

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Demo

Download Ulta Beauty App to try the experience.

Impact

The introduction of the Skin Analysis feature in the Ulta Beauty App represented a significant leap forward in personalized skincare, making it more relevant and accessible than ever:

  • Enhanced Personalization: By leveraging AI, we were able to offer personalized product recommendations, ensuring that each guest received suggestions best suited to their skin conditions and goals.
  • Virtual Skincare Reports: Guests received a virtual skin report with diagnoses and curated recommendations, including tips and options to sort and filter results, providing a comprehensive approach to skincare.
  • Increased Engagement: The AR/AI-driven capability significantly boosted engagement, especially during the pandemic, as guests looked for safe, socially distanced ways to explore and shop for beauty products online. The GLAMLab feature, in particular, saw skyrocketing usage, highlighting its value as a tool for virtual beauty exploration.

Technical Details

Built using mostly Node.js, Typescript, Webpack, and Google Cloud.

Responsibilities

  • Backend Development: Led the development of a robust middleware layer in Node.js and Typescript.
  • API Integration and Personalization: Ensured the effective integration of APIs for skin diagnosis and product recommendations, focusing on AI-driven personalization to match products with user needs accurately.
  • Google Cloud Deployment: Managed the deployment of our service on Google Cloud, optimizing for performance and scalability to support the high demand and deliver a seamless user experience across all devices.

Press & Media Coverage

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