The AI Training Ground for Melanated Skin

Melanin-aware skin data for more accurate skin-health and beauty technology.

Our Mission

To improve how technology understands and serves melanated skin by supporting the development of more accurate, responsible, and inclusive skin-health and beauty tools.

Our Data Approach

Melanoir Labs provides structured, melanin-rich skin imagery and documentation to support model development and evaluation in skin-health and beauty technology, with a focus on acne, hyperpigmentation, texture, and tone variation on deeper skin tones.

Who It’s For

  • Beauty-tech platforms — improve shade matching & analysis
  • Health AI teams — strengthen dermatology model evaluation
  • Product teams — reduce bias in classification and recommendations

What We Do

We create melanin-rich, standardized skin imagery with consistent capture protocols and annotation guidance designed for model training and evaluation.


Focus areas:

  • Acne (inflamed + non-inflamed)
  • Post-inflammatory hyperpigmentation (PIH) + erythema (PIE)
  • Texture and visible tone variation
     

Why It Matters

AI is only as good as the data it’s trained on—and melanin has been underrepresented in many skin datasets. Melanoir Labs exists to help teams improve accuracy, reduce misclassification risk, and build more inclusive skin-health technology.

Data Integrity & Privacy

  • We take privacy seriously
  • Consent-first data collection
  • De-identification practices (e.g., no names attached to images)
  • Intended for internal R&D and model evaluation/training under license

About Our Founder

About Our Founder

Crystal Ochemba is a licensed esthetician and medspa owner with over a decade of experience working hands-on with melanated skin. Through years of treating acne, hyperpigmentation, and texture concerns, she observed a consistent gap in how digital skin tools and AI platforms interpret deeper skin tones.

Melanoir Labs was founded to address this gap by grounding skin data development in real-world clinical practice. Crystal brings a practitioner-first lens to building structured, responsible skin data—focused on accuracy, context, and respect for the communities represented.

Contact Us

Let’s talk about how we can support your team.

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