A structured, high-resolution dataset built for AI/ML teams, research institutions, and enterprise product development.

• First-party, user-annotated data – Every dataset is collected and labeled with a multi-layered quality assurance process to ensure accuracy, consistency, and bias reduction.
• Multi-dimensional data points – Captures skin texture, undertone variations, and environmental factors to enhance AI model performance.
• ‍Available via API & Batch Access – Monthly and annual licensing models allow seamless integration into existing ML workflows.‍
• Comprehensive skin tone representation – Includes darker skin tones and diverse phenotypes, filling a critical gap in the industry.

A high-precision AI model designed to improve color matching, product recommendations, and dermatological assessments.

• Trained on diverse datasets – Addresses bias by incorporating melanin-rich skin data to ensure fair and accurate results across all populations.
• Optimized for real-world applications – Designed for foundation and concealer shade matching, dermatology AI, and digital skin analysis tools.
• Deployable via API or On-Premise – Scalable architecture for real-time processing, batch analysis, or offline deployment in research and retail applications.

An AI-powered system for ingredient discovery, formulation optimization, and procurement intelligence.

• Predictive ingredient matching – AI-driven analysis recommends optimal ingredient combinations based on efficacy, safety, and compatibility.
• Sourcing intelligence – Provides insights into ingredient suppliers, regulatory compliance, and market availability to streamline procurement.
• Customizable to enterprise workflows – Supports integration with R&D databases, supply chain management systems, and product formulation software.