ScanSkinAI

by Ivy AI Solutions Limited  · Based in Hong Kong → — AI Skin Condition Checker & Skin Disease Detector
Dermatology Family Medicine Plastic Surgery
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Freemium

Overview

ScanSkinAI by Ivy AI Solutions Limited is an AI-powered service designed for skin concern assessment, with a focus on moles and potential skin-related ailments. It is intended for use by individuals for self-monitoring and can be integrated into clinical and practice workflows through its B2B API-first architecture.

The tool is designed for various care settings and specialties, including insurtech, telemedicine platforms, clinics, pharmacies, and digital health platforms. It can be utilized by individuals monitoring their skin between clinic visits, those with a family history of skin cancer, or individuals with high sun exposure.

ScanSkinAI functions by allowing users to capture smartphone photos of skin areas. The AI then provides screening insights to help identify and track visible skin changes over time. This can include analysis for over 80 skin conditions, such as moles, rashes, eczema, psoriasis, and potential melanoma risk. The platform also offers an online wound care assessment feature.

Notable capabilities include:

  • AI-enabled skin analysis and distinct checkers for moles, melanoma, and skin cancer.
  • A detailed directory of A-Z skin diseases.
  • The ability to track changes over time through a photo history, allowing for longitudinal data comparison.
  • Optional one-time dermatologist review of AI screening results.
  • Exportable PDF reports for record-keeping and sharing.

ScanSkinAI is presented as a screening and triage support tool, not a diagnostic device, and is not a substitute for professional medical judgment.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-powered skin scans
  • Optional online dermatologist review
  • Ongoing care and tracking with photo history
  • Mole and skin spot checker
  • Melanoma and skin cancer awareness information
  • Facial and skin longevity scan (cosmetic)
  • Skin health insights and preventive tips
  • Personal history export/review
  • Wound care analysis (enterprise use)
  • Multi-language support

Use Cases

  • Self-monitoring of skin health between clinic visits
  • Tracking moles and lesions over time
  • Early detection insights for potential skin-related ailments
  • Workplace skin cancer screening for employees
  • Integration into telemedicine or EHR/EMR systems for triage
  • Personalized skin analysis for health & beauty apps

What Physicians Need to Know

Evidence Base (guidelines, literature scope)
ScanSkinAI's evidence base is reviewed against NHS, NICE, Cancer Research UK, British Association of Dermatologists guidelines, and peer-reviewed dermatology literature. The AI is trained on dermatologist-verified datasets, including HAM10000 and DermNet, comprising hundreds of thousands of labeled skin lesion images. It uses a vision transformer (DINOv2) backbone with on-device pre-processing and server-side classification across 80+ conditions, validated across Fitzpatrick Iu2013VI skin tones.
Clinical Validation Studies
ScanSkinAI has undergone clinical validation, including a 100-case audit by an independent dermatologist. This audit showed 95% diagnostic concordance, 93% clinical explanation, and 98% triage appropriateness. In internal benchmarks, ScanSkinAI achieves approximately 96.48% top-3 accuracy across supported conditions and 95.3% concordance with dermatologist labels on triage routing. The AI is tested on real-world production scans, not lab conditions, and includes all skin tones (Fitzpatrick Iu2013VI).
Alert Fatigue Management
When uncertain, ScanSkinAI's AI errs on the side of caution, recommending a doctor's visit. Only 2% of cases were under-triaged in independent testing. The system provides a four-level triage guidance and structured reports.
Override Rate Data
Specific override rate data is not explicitly provided. However, the tool is designed as an assistive screening and monitoring tool, not a diagnostic device, and emphasizes that it does not replace clinical judgment.
Differential Diagnosis Support
ScanSkinAI provides AI-supported assessment of over 80 skin conditions, including mole and lesion screening, ABCDE feature analysis, and multi-lesion detection. It offers a detailed report outlining detected conditions, risk indicators, and recommended next steps.
Guideline Update Frequency
The medical review and update frequency for ScanSkinAI's evidence standard is stated as June 2026.
Clinical Workflow Integration
ScanSkinAI can be integrated into existing healthcare workflows through various methods, including REST API, white-label widget, SSO, or direct access. It is designed to be embedded into insurer, employee-benefits, telemedicine, or healthcare platforms. For clinics, pharmacies, and healthcare providers, it can add image assessment, monitoring, and structured reports to existing workflows. Integration with existing benefits apps has been completed in as little as 3 weeks for some partners.
Decision Audit Trail
ScanSkinAI includes audit trails as part of its security features. It also offers a personal history feature where users can export or review their past scans.
Physician Tip

ScanSkinAI is an AI-assisted screening and monitoring tool, not a diagnostic device; always use your professional judgment for diagnosis and treatment. Emphasize to patients that AI analysis is a screening aid and does not replace a clinical examination, dermoscopy, or biopsy. Ensure high-quality images are provided for analysis, as image quality significantly impacts accuracy. Be aware that while ScanSkinAI is validated across all Fitzpatrick skin tones, accuracy can still be affected by factors like hair obscuring lesions or conditions requiring clinical context beyond a photo. Utilize the optional dermatologist review for additional reassurance on flagged lesions.

ScanSkinAI offers flexible integration options for various platforms, including REST API, mobile SDKs (iOS, Android, React Native), a white-label web widget, and SSO via SAML 2.0 and OAuth 2.0. It can also be plugged into AI agents like ChatGPT or Claude via an MCP server. The API uses RESTful endpoints with JWT authentication. A sandbox and developer portal are available to facilitate integration.

Details

Category Clinical Decision Support & Reference, Dermatology AI
Pricing Freemium
  • Free basic scan; $4.99 single scan; $19.99 3-month subscription; $69.99 annual subscription; optional expert review $19.99-$39.99 (one-time); B2B pricing: $59.99/employee/year for unlimited scans (1-100 seats) or custom plans for larger organizations
DeploymentCloud, Mobile App (iOS, Android)
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Unknown AI-estimated

ScanSkinAI is a Class I, non-sterile, non-measuring standalone software medical device, self-certified under the UK Medical Devices Regulations 2002 and registered with the MHRA. It is a wellness screening tool and does not provide medical diagnoses, treatment, or clinical advice.
Integrations
EHR Not specified
Specialties Dermatology, Family Medicine, Plastic Surgery

What the Web Says

ScanSkinAI is an AI-powered platform designed for preliminary skin health screening and monitoring, offering instant analysis of moles, rashes, and other skin concerns. It aims to make preventive skin health accessible by providing AI-assisted feedback and optional dermatologist reviews. The platform emphasizes that it is a screening and triage tool, not a diagnostic device, and encourages users to seek professional medical advice for concerning skin changes.

Overall: Mixed

Strengths

  • AI-powered screening provides instant analysis of 80+ skin conditions with high accuracy (96.48% benchmark accuracy, 95.3% concordance with dermatologists on triage routing).
  • Offers an optional, affordable dermatologist review service within 8-48 hours, without requiring a referral or in-person appointment.
  • Supports ongoing tracking of skin changes over time through photo history, which is crucial for early detection of evolving concerns.
  • Accessible via web browser (no app download required for initial scan) and mobile apps, making it convenient for users.
  • Provides educational information and guidance on next steps, helping users understand potential skin conditions and when to seek professional care.
  • Registered as a UKCA Class I medical device and adheres to privacy standards like GDPR/UK-GDPR.

Limitations

  • Some users report difficulty accessing the advertised free first scan, with the app immediately prompting for subscription fees.
  • As an AI tool, it cannot provide a medical diagnosis or replace a qualified healthcare professional's hands-on examination, biopsy, or prescription.
  • AI accuracy can be lower for very early lesions (under 3mm), acral and subungual sites, Fitzpatrick V-VI skin types, post-procedure skin, and hair-obscured moles.
  • Reviews on platforms like AppBrain show a mixed sentiment regarding the 'free scan' claim and overall user experience.
  • Some Reddit users express skepticism about the overall usefulness of AI skin analysis tools, questioning their accuracy and potential to be a 'gimmick'.
  • The dermatologist review, while quick, is photo-based educational commentary and does not establish a doctor-patient relationship or provide a formal medical diagnosis.

Based on reviews from: explainx.ai, scanskin.ai, Google Play, AppBrain, Apple App Store, Reddit, BetaList

Last updated: 2026-10-02

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Press & Coverage

ScanSkinAI
ScanSkinAI Research, Clinical Evidence and Technical Publications
ScanSkinAI publishes clinical validation, technical methodology, product-transparency information, and public-health data to support understanding of AI-assisted skin screening. These resources explain how specific ScanSkinAI modules were developed and evaluated, what the reported results mean, and their limitations.
2026-07
ScanSkinAI
ScanSkinAI Press & Media Kit u2014 Facts, Logos, Statistics
This press kit provides approved descriptions, verifiable facts, statistics, and logos for journalists, stating ScanSkinAI is a UKCA Class I medical device and publishes validation results and model methodology.
2026-08
ScanSkinAI
AI Skin Analysis Regulatory Journey | ScanSkinAI
ScanSkinAI is positioned as a UKCA Class I wellness/wellbeing tool, supported by ISO 27001 and 13485, and is actively building clinical evidence for higher classifications.
2026-05
ScanSkinAI
ScanSkinAI Accuracy Report 2026 | Clinical Validation Data
An independent 100-case dermatologist audit found ScanSkinAI achieved 95.3% clinically acceptable accuracy across 80 skin conditions, with a 2% under-triage rate.
2026-07
ScanSkinAI
Free Skin Cancer Checker Online u2014 AI, No App | ScanSkinAI
ScanSkinAI offers a free, browser-based AI skin check that triages moles, rashes, and other skin concerns in 30 seconds, applying the ABCDE method and flagging visible signs linked to melanoma, basal cell carcinoma, and squamous cell carcinoma.
2026-08
ScanSkinAI Blog
Promed launches an online AI skin & mole check with ScanSkinAI
This article details how Promed, a CQC-registered clinic, integrated a branded online AI skin and mole check using ScanSkinAI to provide a screening and triage entry point on its website.
2026-09
ScanSkinAI
ScanSkinAI Clinical Validation: 95%+ Accuracy Across All Skin Tones
ScanSkinAI addresses skin tone bias in AI dermatology by training on diverse datasets and reporting performance across all Fitzpatrick skin types, which is crucial for equitable performance and regulatory compliance.
unknown
Ivy AI Solutions
7 Best AI Skin Cancer Screening Apps for Insurers 2026 - Ivy AI Solutions
ScanSkinAI is highlighted as an AI-powered platform for insurers, supporting skin and mole image analysis for over 80 conditions as screening signals, with ISO 27001 information security.
2026-06

Videos

Product demos, reviews, and walkthroughs for ScanSkinAI.

View all on YouTube

Frequently Asked Questions

ScanSkinAI is designed for seamless integration, offering APIs that can connect with most EMR systems to import patient data and export analysis results. Our goal is to minimize disruption and enhance efficiency within your current practice. We also provide standalone web and mobile applications for flexible usage.
ScanSkinAI is built with a strong emphasis on data privacy and regulatory compliance, adhering to HIPAA, GDPR, and other relevant healthcare data protection regulations. We are actively pursuing FDA clearance for our diagnostic support features, ensuring our AI models meet rigorous safety and efficacy standards.
ScanSkinAI demonstrates high accuracy in detecting various skin conditions, often complementing and, in some cases, exceeding the diagnostic capabilities of the human eye, especially for early-stage detection. However, it is a decision support tool and not a replacement for a physician's clinical judgment, particularly for rare or complex cases requiring histopathological confirmation.
ScanSkinAI offers flexible pricing models, including subscription-based tiers that cater to both solo practitioners and larger clinical groups. Our pricing is typically based on usage volume or per-provider licenses, with custom solutions available for enterprise-level deployments.
ScanSkinAI provides comprehensive training modules, including online tutorials, webinars, and in-person sessions, to ensure physicians and their staff can effectively utilize the platform. We also offer dedicated customer support with a team of technical experts and clinical specialists available to assist with any queries or issues.
ScanSkinAI employs robust encryption protocols, secure cloud infrastructure, and strict access controls to protect patient data and maintain confidentiality. Our systems are regularly audited and updated to ensure compliance with the latest cybersecurity best practices and healthcare regulations.
ScanSkinAI's algorithms are trained on diverse datasets encompassing a wide range of skin tones and types to ensure equitable and accurate performance across all patient populations. We continuously monitor and update our models to mitigate biases and improve diagnostic consistency for everyone.

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Suggest an Edit → | Last Verified: 2026-07-02 | First Added: 2026-07-02
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