Multi-Race 3D Data
We train our algorithms on vast, multi-ethnic 3D datasets to master the complexities of different skin tones and ages. This rigorous training eliminates bias and guarantees precision across all demographic groups.
Accelerate Skin Science
Innovation with AI-Driven Rigor
Transforming 10M+ skin data points into actionable R&D insights. We provide the precision, consistency, and expert intelligence needed to move from concept to market-ready claims faster.
Trusted By
10M+
ANNOTATED DATA
5.4M+
SKIN ANALYSIS REPORTS
141K+
MONTHLY SCANS
Pioneering Multimodal Algorithms for Actionable Skin Insights
LLM-Powered Skin Analysis Agents
We enable users to interact through natural language, image selection, photos, or text prompts. Our LLMs understand and decompose tasks to orchestrate downstream modules for a coordinated response.
High-Precision 3D Facial Reconstruction
We integrate 2D segmentation, 3D point clouds, and multispectral data for advanced facial editing to create an interface with precise control over angles, structures, and textures.
The Voice of Science
"By integrating deep learning with dermatological expertise, Evelab Insight offers unparalleled diagnostic depth. It is an indispensable asset for future-ready clinics focused on skin science."
Dr. Fudi Wang
Chief Scientist, EveLab Insight
Ph.D. in Computational Biology, Chinese Academy of Sciences | Former Postdoctoral Fellow, Stanford University School of Medicine | Core Member, Lab-SADS
"The sophisticated AI algorithms of Evelab Insight based on precise, quantitative data processing can remarkably visualize deep-layer skin concerns and track solution efficacy. It offers the reliable evidence-based foundation needed for high-level dermatological practice and future-ready clinics focused on skin science."
Dr. Zhao Kejia
Renowned Dermatologist
Ph.D. in Dermatology, Zhejiang University | Former Postdoctoral Fellow, University of Maryland, College Park | Former Postdoctoral Fellow, Medical University of South Carolina
World-Class Algorithmic Excellence
2018
ECCV PIRM Image Enhancement Challenge
2018
ISIC Skin Lesion Segmentation Challenge
2019
NTIRE Image Dehazing Challenge
2019
NTIRE Image Enhancement Challenge
2021
Tencent "Mi Ying" Medical Artificial Intelligence Algorithm Competition Multi-Disease Auxiliary Diagnosis of Fundus Color Photography
2016
FDDB Accuracy of Facial Algorithm
2018
ECCV PIRM Image Enhancement Challenge
2018
ISIC Skin Lesion Segmentation Challenge
2019
NTIRE Image Dehazing Challenge
2019
NTIRE Image Enhancement Challenge
2021
Tencent "Mi Ying" Medical Artificial Intelligence Algorithm Competition Multi-Disease Auxiliary Diagnosis of Fundus Color Photography
2016
FDDB Accuracy of Facial Algorithm
Academic Research
2026MICCAIConference
Skin2Mind: A Multimodal Framework for Mental Health Risk Screening via Facial Images and Structured Skin Reports
Jiahe Liu et al.
2026Scientific ReportsJournal
Facial dermal exposure-related parameters and skincare behaviors among adult women from six cities in China
Rong Hu et al.
2026SIDConference
Prediction of skin biophysical parameters from facial images using deep learning in large-scale population cohorts
Fudi Wang et al.
2025JIDJournal
GWASs of the Nasolabial Fold Identified Variants Related to Genes that Also Affect Facial Morphology
Fudi Wang et al.
Ready to Transform Your Skin Data into Innovation?
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