Clinical Studies Software is the name of Haut.AI’s premier skin intelligence offering a platform that is clinically validated to bring research in dermatology and cosmetics to the present day. The software was developed for skincare brand developers, ingredient makers, and CROs, and it enables the management of clinical trials involving several hundred or even thousands of subjects in clinical, decentralized, and at-home clinical trial settings.
Using standardized computer vision together with advanced machine learning algorithms, the platform assesses 48 biomarkers, including deep wrinkles, hyperpigmentation, skin texture, severity of acne, erythema, and pore structure. The platform decreases clinical launch preparation time from 8 to 16 weeks in a traditional way to 2 or 3 days only.
Overcoming Legacy Friction in Clinical Skin Evaluation
For decades, dermatological efficacy testing has been bottlenecked by rigid laboratory requirements, expensive hardware setups, geographically restricted candidate pools, and subjective human grading. Typical clinical skin studies have historically been constrained to cohorts of just 30 to 35 subjects. Beyond high operational expenditures, human assessment introduces inter-grader variance, where different experts or even the same clinician over time assign inconsistent scores to identical skin conditions.
Haut.AI’s platform eliminates human grader bias by enforcing a single, standardized algorithmic baseline across every image, location, and evaluation period. By enabling trial participants to submit remote facial captures that match the precision of laboratory-grade photography, R&D teams can now execute statistically robust, multi-region research programs at scale.
“Clinical research in beauty and skincare has reached an inflection point,” said Anastasia Georgievskaya, CEO and Co-Founder of Haut.AI. “The industry has incredible expertise in clinical science, but the tools used to collect and analyze data have remained largely unchanged for years. Our goal is not to replace clinical studies. It’s to enhance them by making skin measurable at scale. R&D teams that can measure continuously across larger populations don’t just do better science; they make faster decisions.”
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High-Precision Validation and Repeatability Benchmark
Developed in close technical collaboration with board-certified dermatologists, Haut.AI’s skin evaluation models underwent rigorous benchmark testing at the Institut d’Expertise Clinique (I.E.C.).
In comparative trials evaluated against consensus expert panels, the platform achieved Intraclass Correlation Coefficients (ICC) ranging between 0.97 and 0.98 across five core facial skin endpoints a score reflecting near-perfect statistical consistency. Crucially, this level of correlation held firm regardless of whether imagery was recorded using dedicated medical hardware or captured directly by participants on personal smartphones.
“Visible skin aging has always been harder to quantify with the same rigor we apply to molecular aging markers,” said Varun Dwaraka, PhD, FRSB, Director of Research and Principal Investigator at TruDiagnostic. “Haut.AI’s Clinical Studies Software gave us standardized, image-derived measures of facial aging traits that we could pair directly with our DNA methylation data. That combination let us treat visible aging as a quantitative trait alongside our biological measurements, instead of relying on subjective grading.”
End-to-End Workflow Optimization
The platform digitizes and unifies the clinical trial lifecycle across five distinct architecture layers:
- Protocol Architecture: R&D directors configure candidate registries, multi-stage timelines, submission cadences, photo capture parameters, and embedded subject surveys within a centralized command center.
- Precision Image Capture: Trial candidates record standardized photos remotely or on-site through Haut.AI’s proprietary LIQA™ (Live Image Quality Assurance) technology, ensuring real-time lighting and framing compliance.
- Multi-Marker Measurement: Algorithmic pipelines score 48 validated dermatological endpoints automatically.
- Cohort Analytics: Researchers track longitudinal trends, segment skin phenotypes, and assess product efficacy through interactive, cohort-level dashboards.
- Claims Substantiation: Raw analytics automatically compile into regulatory and marketing-ready evidence packages to support performance claims and consumer communications.
Lowering Trial Expenses While Expanding Scale
Conventional efficacy testing accumulates significant recurring costs across manual grading, routine site monitoring, administrative tracking, and labor-intensive reporting. By automating visual scoring and enabling remote submission workflows, Haut.AI drastically shrinks per-participant operational overhead.
According to enterprise bench tests, organizations deploying the platform across an average of six studies per year realize a 3x return on investment (ROI), reallocating capital toward larger subject cohorts rather than repetitive administration.
Enterprise Provenance and Data Protection
Haut.AI’s core technology is already deployed by major global personal care enterprises, active ingredient suppliers, and luxury cosmetic conglomerates. Commercial deployments to date include:
- Pre-screening trial cohorts exceeding 7,000 global participants for a multinational personal care group.
- Multi-year longitudinal skin research projects sponsored by Fortune 500 beauty manufacturers.
- Global formulation and active ingredient validation programs across diverse demographic markets.
To protect subject confidentiality, all facial imagery processed by the system undergoes automatic anonymization via Haut.AI‘s patented Skin Atlas technology, keeping personally identifiable information (PII) segregated entirely within the client’s secure database.
