01 In a lab 
Controlled high-resolution imaging
A high-resolution imaging device captures images under fully standardized conditions.
Built for claims-ready science
Clinical Studies Software for remote AI-enabled skin research
Clinical skin studies are limited by on-site capacity and cohort size. Haut.AI runs remote efficacy studies on cohorts of 100 to 7,000 participants, with AI skin analysis and claims-ready reporting. Setup in 2–3 days.
100–7,000 participants per study
48 metrics face · hair · body
Haut.AI powers skin analysis for leading global brands
Measurement you can trust outside the lab
The AI grading model achieves ICC values of 0.97–0.98 across all capture settings (clinical camera, clinic smartphone, and at-home selfie), meaning results replicate reliably across participants, sites, and time points.
One consistent, validated measurement
Your study no longer has to happen in one place
A clinical skin study now spans three capture settings: a controlled lab, a study clinic, and a participant's home. Haut.AI's measurement layer returns consistent results across all three, so your cohort is not limited by who can travel to a site.
02 At a clinic 
Semi-controlled clinic capture
A smartphone captures images under standard indoor lighting at a research site.
03 At home 
Fully uncontrolled at-home capture
The participant captures a smartphone selfie in their own environment, without any lighting or positioning control.
Measurement you can trust outside the lab
Accuracy measured against trained dermatologist grading panels
Capturing skin anywhere only matters if the scores stand up. Haut.AI's automated grading has been validated against trained dermatology panels, repeats reliably across participants and time points, and holds across diverse cohorts.
Dermatologist-aligned grading
Validation work with independent clinical research partners demonstrated high correlation between Haut.AI's automated scoring and trained dermatology grader panels.
Excellent repeatability
The AI grading model achieves intraclass correlation (ICC) values in the excellent range (≥ 0.90), meaning results you can replicate across participants, sites, and time points.
Validated across diverse participants
Validation conducted across participants aged 20 to 70, balanced gender, covering the demographic range your study cohorts are likely to span.
Bring a claim you want to make. We'll show the endpoints that support it.
Book a demo 48 measurable skin parameters
Choose your endpoints from a validated metric library
Every study endpoint maps to a specific, measurable parameter. Select what is relevant to your study and Haut.AI matches the measurement to your design.
Acne and breakouts
Acne-inflammationBreakoutsPimplesPapulesPustulesIrritationPost-acne hyperpigmentation
Lines and wrinkles
LinesCrow's-feet linesDeep linesEye linesFine linesGlabellar linesMarionette linesNasolabial wrinklesUnder-eye lines
Pigmentation and tone
Dark circlesFrecklesMelasmaPigmentationRednessSun spotsSkin toneITA
Pores and texture
Enlarged poresPoresUniformnessSkin type
Aging and structural
Perceived ageEyes ageEyes puffinessSaggingJowlsLacrimal groovesMoles
Color
Hair colorColor uniformnessTreatment detection
Health and condition
DamageDensityFrizziness
Geometry and structure
CurlinessGathered hairLengthVolume
Acne and breakouts
Breakouts
Pigmentation and tone
ITAPigmentationRedness
Texture and surface quality
LinesMicroscalingThickeningUniformness
Face29 measurable parameters
How data collection works From study setup to insights
From study setup to insights
on one platform
You bring the panel. Haut.AI handles capture, AI skin analysis, and export. Participants need no app, only a link.
1
Create a study
Choose endpoints, stages, and capture settings in the platform.
2
Invite participants
Enter your panel and start the study for everyone at once.
3
Capture data
A no-code link guides participants through Live Image Quality Assurance™ (LIQA™) technology, checking position, lighting, and framing in real time before capture. No app required. Repeat sessions are supported.
4
Monitor in real time
Track completion and AI skin analysis results on a live cohort dashboard.
5
Analyze and generate insights
Review scoring and trends across all endpoints, time points, and study arms.
Setup to study start in 2–3 days.
Study designs
Five study designs your team can run today
From a 4-week ingredient screen to a 12-month longitudinal track, the platform supports the full range of study designs: on-site, remote, or hybrid.
1 Ingredient efficacy Exploratory · Example claims
Mechanism-matched metrics, e.g. pigmentation for niacinamide, wrinkle depth for retinol, sagging for peptides.
Active X reduced under-eye pigmentation by 23% at 8 weeks (p<0.05).
2 Finished product efficacy Example claims
Multi-metric panel matched to marketed benefits.
After 8 weeks, 87% of participants showed measurable improvement in skin texture and tone.
3 Comparative claims (split-face) Example claims
Metric comparison between treated and untreated zones, or product A vs. B.
Outperforms comparator by 18% in fine-line reduction at 8 weeks (p<0.05).
4 Perception vs. objective measurement Example claims
AI measurement paired with a consumer perception panel or expert grader panel.
92% perceived radiance improvement; AI confirmed measurable reduction in pigmentation density.
5 Longitudinal Exploratory · Example claims
Trajectory analysis across continuous remote captures.
Sustained reduction in photo-damage signs over 12 months of consistent use.
Mechanism-matched endpoints
Active → metric mapping · 8-week read
Niacinamide → Pigmentation−23%
Retinol → Wrinkle depth−17%
Peptide → Sagging−12%
Vitamin C → Uneven tone−19%
Cohort dashboard
n = 312 · finished product · week 8
87%improved
312valid subjects
p<.05significance
Texture+21%
Tone uniformity+16%
Radiance+13%
Split-face comparison
Treated vs. control zone · fine lines
Fine-line reduction+18%
Perception vs. objective
Consumer panel vs. AI measurement
Perceived radiance92%
AI: pigmentation ↓−21%
Perceived firmness81%
AI: sagging ↓−11%
PerceptionAI measurement
Longitudinal trajectory
Photo-damage index · 12-month remote capture
Photo-damage signs (lower is better)
Exploratory · Example claimsStudy design 01 / 05
Ingredient efficacy
−23%under-eye pigmentation at 8 weeks · p<0.05
Endpoints
Mechanism-matched metrics, e.g. pigmentation for niacinamide, wrinkle depth for retinol, sagging for peptides.
Example claimsStudy design 02 / 05
Finished product efficacy
87%of participants showed measurable improvement at 8 weeks
Endpoints
Multi-metric panel matched to marketed benefits.
Example claimsStudy design 03 / 05
Comparative claims (split-face)
+18%vs. comparator, fine-line reduction · p<0.05
Endpoints
Metric comparison between treated and untreated zones, or product A vs. B.
Example claimsStudy design 04 / 05
Perception vs. objective measurement
92%of participants perceived radiance improvement
Endpoints
AI measurement paired with a consumer perception panel or expert grader panel.
Exploratory · Example claimsStudy design 05 / 05
Longitudinal
12 mosustained photo-damage reduction
Endpoints
Trajectory analysis across continuous remote captures.
Fast applications
From screening to formula validation in weeks. All on the same platform.
The same platform supports faster, lower-commitment applications, from same-day screening to 4-week formula checks.
Subject pre-screening
Remotely screen candidates against inclusion/exclusion criteria before enrollment. Auto-stratify by demographics, Fitzpatrick, and baseline skin metrics.
Cohort100–2,000
DurationDays
OutputPre-qualified subject list, balanced cohorts
Ingredient proof-of-concept
Test candidate actives head-to-head for biological response before committing to a larger study.
Cohort20–60 / active
Duration2–4 weeks
OutputEffect-size ranking across candidates and metrics
Formula iteration tracking
Track hydration and redness across formulation versions with a tight feedback loop for formulators.
Cohort15–30
DurationInstant to 3 weeks
OutputComparative metric trajectories per formula version
Reformulation & batch validation
Confirm that a reformulated product, manufacturing batch, or new SKU performs against established benchmarks.
Cohort20–50
Duration4–6 weeks
OutputPass/fail vs. pre-set threshold
Study economics
The case for running your next study at a larger scale
Clinical skin studies typically produce limited statistical confidence at significant cost. Haut.AI-powered studies reduce site variability through automated AI grading and make larger cohorts practical through remote capture.
3×average ROI
Haut.AI-powered studies replace manual grading, monitoring, and operational overhead, returning on average three times their cost.
Based on an average of 6 studies per year.
| Current standard | Haut.AI-powered | |
|---|---|---|
| Participants number | 30–40 participants | 100–7,000+ participants |
| Setting | On-site only | On-site, remote, or hybrid |
| Time points | 3–8 | Continuous |
| Statistical significance | Low (small cohort) | High |
| Study site variability | High | Low to none |
| Grading | Human experts (variable agreement) | Automated AI (consistent) |
| Cost | $$$$ | $$ |
Faster decisions
Run an ingredient proof-of-concept in 2–4 weeks, not quarters.
Bigger cohorts, comparable spend
Remote capture removes per-participant site visit costs. Run at a significantly larger scale for comparable total spend.
Statistically stronger evidence
Larger cohorts, more time points, and consistent AI grading produce tighter confidence intervals and more defensible claims.
Your data, your IP
Images, measurements, and study results are your property. Full export at any time. Annual SaaS license with no per-study gate fees.
Get a cost and timeline estimate for your next study.
Book a call How it works
How a study works with Haut.AI
From study design to claims-ready report, Haut.AI manages the measurement and analytics layer. Your existing team or research partner handles the operational side.
From signed protocol to data capture typically takes two to four weeks. The full process from kickoff to claims-ready report depends on study duration, with final reporting delivered within two weeks of study completion.
Image capture, image quality assurance, automated AI analysis, cohort analytics, and the final report. In fully remote studies, Haut.AI handles the complete measurement pipeline.
Yes. Haut.AI can operate as a technology partner alongside your CRO. We provide software training for their team and technical documentation for IRB submissions.
You do. All images, derived measurements, and study results remain your property. Full export is available at any time.
Statistical analysis, per-subject and cohort visualizations, and optional SkinGPT simulation visuals showing projected product effects on skin.
FAQ
Frequently asked questions
Do you have more questions or need support? Send us a message and we will be happy to help.
Contact usHaut.AI's clinical software covers 29 face metrics, 10 hair metrics, and 9 body metrics, 48 parameters in total. Face metrics span acne and breakouts, lines and wrinkles, pigmentation and tone, pores and texture, and aging and structural signs. Hair metrics cover color, health and condition, and geometry. Body metrics cover breakouts, pigmentation, and texture and surface quality.
Yes. Haut.AI's LIQA technology guides participants through smartphone image capture in real time, checking position, angle, lighting, and framing before the image is taken. This ensures consistent image quality across remote and uncontrolled settings. Validated performance has been confirmed at home as well as at a clinical site.
Haut.AI integrates into your existing study structure. Your CRO retains responsibility for ethics, IRB, protocol adherence, GCP compliance, and subject recruitment. Haut.AI provides the measurement and analytics layer. We support a 3-way partnership model and provide software training for your CRO team.
Ingredient efficacy, finished product efficacy, comparative claims (split-face), perception vs. objective changes, and longitudinal tracking. The same platform also supports faster pre-study applications: subject screening, ingredient proof-of-concept, formula iteration tracking, and reformulation validation.
Haut.AI's LIQA (Live Image Quality Assurance) technology runs a real-time guided capture process before the image is taken, not after. It checks positioning, lighting, and framing and prompts the participant to correct before submitting. A backend quality check runs additionally. This means the AI receives usable data from the first submission.
Yes. The platform accepts uploads from VISIA, ColorFace, and other imaging platforms, with file names auto-parsed. This means existing on-site imaging setups can feed directly into Haut.AI's analysis and cohort dashboard without re-capturing.
Everything the measurement layer covers
Remote and on-site data collection 48 measurable skin parameters Automated AI analysis Real-time cohort dashboard Dermatologist-aligned grading Claims-ready reporting CRO-compatible by design You own your data
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Get in touch
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- Send us an e-mail
- team@haut.ai
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- press@haut.ai
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