Product Overview
Legit.Health is a clinical AI platform that automatically diagnoses and measures the severity of skin and wound conditions. It is a certified medical device deployed in 7 markets, used by pharma companies, hospital groups, and insurance networks.
59 AI models in production · 300+ pathologies diagnosed · 22+ clinical severity scales · CE · ANVISA certified · UK MHRA (Class I)
What it does
Dermatology faces two structural problems: there are not enough specialists, and severity assessment is subjective and inconsistent. Both problems cost money: waiting lists run 3-4 months in public health systems, and pharma trials are put at risk because manual PASI/EASI scoring carries 20-30% inter-rater variability, which inflates variance and weakens statistical power.
Legit.Health solves both with a platform that covers the full clinical workflow:
- A patient or non-specialist submits an image.
- The AI supports diagnosis of the condition (300+ pathologies via ICD-11), scores severity on validated clinical scales, flags urgent referral cases, and returns a structured clinical report in seconds.
- The output integrates into the customer's existing system via API, deep link, or standalone web app.
The result is objective, reproducible, audit-ready clinical data at the point of care and at the scale of a clinical trial.
Platform capabilities
Diagnosis Support
Multi-class classification of 300+ conditions via ICD-11, with binary urgency flags (urgent referral ≤48h, high-priority ≤2 weeks, malignancy suspicion). Enables non-specialists to triage accurately.
Automatic Severity Assessment
Quantifies severity on 22+ clinical scales (PASI, EASI, SCORAD, IHS4, GPPGA, AUAS, SALT, AWOSI, and more). Reduces inter-rater variability in clinical trials and routine monitoring.
Smart Referral
AI-assisted triage helps GPs decide whether a patient needs specialist referral. Reduces unnecessary referrals, shortens waiting lists, and decreases burden on dermatology departments.
Treatment Success Prediction
Beyond measuring current severity, the platform can predict patient response to therapeutic decisions. Critical for biologics titration in psoriasis, atopic dermatitis, and HS pharma studies.
Image Quality Assurance
DIQA model scores image quality 0-10 with dimension-level subscores before analysis. Ensures clinical-grade reliability at scale: catches poor images before they corrupt trial data.
Patient and Doctor App
Web application for direct patient access: self-monitoring, condition tracking, and treatment adherence. Also used by clinicians for real-time assessment outside the clinic setting.
Who uses it and why
Five distinct stakeholders face the same structural problem from different angles. Each generates a different contract type and ACV.
General Practitioners
"I know what the disease is, but I don't know how severe it is."
GPs need severity data to prescribe treatments and refer adequately. The platform automatically scores severity at clinical-grade accuracy, empowering non-specialists to provide a higher degree of care and reducing reliance on the most scarce resource: the dermatologist.
Hospital Managers
"I need the right patient to see the right specialist at the right time."
Smart referral triage reduces waiting lists and doctor burnout by filtering which patients genuinely need a dermatologist appointment. For Sanitas/BUPA, this translated into a reduction from 127 days average wait to objective triage-based prioritisation, with 0% churn since deployment.
Clinicians
"I wish I knew how a patient is going to respond to a specific treatment."
Treatment success prediction and longitudinal severity tracking enables clinicians to monitor patients between visits and adapt therapeutic decisions. It also reduces costs and increases patient safety by catching non-responders early.
Pharma (Clinical Trials)
"Inter-rater variability in PASI scoring is a known endpoint integrity risk."
Manual PASI scoring in Phase 2-3 trials has 20-30% variability between raters. Legit.Health replaces or audits manual scores with objective AI measurement, reducing noise and strengthening statistical power. Johnson and Johnson (psoriasis Phase 3), Boehringer Ingelheim, Eli Lilly, and Pierre Fabre are active customers. Average contract: €50K-€130K TCV per study.
Patients
"I don't know what is going on."
The web application gives patients immediate, objective insights about their condition wherever they are. It reduces anxiety, improves adherence to treatment, and generates longitudinal data that benefits the clinician on the next visit.
How it integrates
Legit.Health is designed to embed into existing clinical workflows, not replace them. Three integration tiers serve different customer needs:
Integration
Deep link
A URL-based trigger that launches the Legit.Health interface from within an existing EHR or hospital system. Minimal integration effort. Results returned in-context. Preferred by hospital groups and insurers.
Integration
API
REST API for full programmatic integration. Pharma companies and large hospital networks embed the AI models directly into their platforms and trial management systems. Returns structured JSON with scores, flags, and confidence values.
Standalone
Web app
A fully functional web application at app.legit.health for use without any integration. Ideal for piloting, telemedicine workflows, patient self-monitoring, and smaller clinical practices.
Business model
Model
B2B SaaS
Annual recurring license (ARR) plus one-time setup and integration fees. License is priced per patient volume or per study.
ACV ranges by segment
Hospital / Insurance: €15K-€85K/yr
Pharma (per study): €50K-€130K TCV
Multi-study frames: €200K-€500K+ TCV
Revenue structure
~66% recurring (ARR layer)
~34% project-based (pharma, integrations)
0% pharma multi-year churn to date
See also
- AI Algorithms Catalogue: All 59 models in production, by clinical category
- Clinical Evidence: 9 peer-reviewed publications validating the algorithms
- Commercial Metrics: ACV breakdown, customer segments, retention
- IP Assets: Patents, trademarks, and proprietary datasets