Since 2022, the Skin & Digital Summit (du Crest et al, 2023a), supported by the Magic Wand Initiative (Inkwood Research, 2025) and New Ideas in Medicine (Inkwood Research, 2025), has been at the forefront of showcasing digital innovations at the intersection of dermatology, esthetics, and skincare. These advancements are rapidly redefining how we diagnose, treat, and educate about skin conditions (du Crest et al, 2023b). Entrepreneurs leading this transformation are leveraging cutting-edge digital technologies to address unmet needs, improve clinical outcomes, and streamline care delivery and information dissemination.
This article delves into the stories of start-ups featured in 2024, highlighting their innovative business models and contributions to the future of our fields. These start-ups span a variety of solutions, including online dermatology services, artificial intelligence (AI)–driven software for the beauty industry, smartphone-based imaging solution, telehealth solutions for men’s health, AI-powered dermatology support, skin analysis software, and teledermatology platform.
The narratives, presented by the entrepreneurs themselves, offer concise updates on their approaches to unmet needs, including the context, proposed solutions, and current limitations. Each section was authored by the respective entrepreneur, with support from the associated companies.
Skindr: Online Dermatologic Consultation Platform
Context
Belgium faces a significant challenge in dermatology care: long waiting lists and a shortage of dermatology professionals lead to slow access to dermatology care (Lambert et al, 2025). This often results in delayed diagnoses and treatments, contributing to patient frustration and increased disease burden, and cost to society. Despite the demand, traditional in-office consultations cannot scale to meet the needs, especially for common dermatologic conditions that require rapid and efficient intervention.
Solution
Skindr (Skindr, 2024) is transforming dermatology care by becoming Belgium's largest online dermatology clinic. Designed to provide fast and effective care, Skindr leverages a user-friendly mobile application that enables patients to upload images of their skin concerns. Certified dermatologists evaluate these images, communicate directly with patients through the application, ask follow-up questions if needed, provide prescriptions, and manage ongoing follow-up care.
Skindr offers a streamlined approach to dermatologic consultations, significantly improving efficiency for physicians and patients alike. The platform optimizes the time spent by dermatologists, allowing fewer professionals to deliver more consultations in less time, ensuring better, faster, and more accessible high-quality care. Skindr has already facilitated over 35,000 consultations, demonstrating its scalability and effectiveness in addressing Belgium's dermatology care gap.
Skindr’s key advantage lies in its speed and efficacy. By removing the logistical barriers of traditional office visits, it allows patients to receive expert evaluations and prescriptions without the typical wait times, all while ensuring that the quality of care remains uncompromised.
Limitations
Although Skindr is a breakthrough in digital dermatology, challenges remain in expanding the platform to address complex cases that may require in-person examinations or advanced diagnostic tools. Future iterations aim to integrate AI for triaging cases and assisting dermatologists, further enhancing care delivery and efficiency.
Skin Match: AI-Driven Software Solutions for The Beauty Industry
Context
The beauty and skincare industry faces a growing demand for transparency and personalized experiences (Mintel, 2023). Salons, spas, and dermatology offices often struggle to provide tailored product recommendations that align with their customer's unique needs, sensitivities, and preferences. This gap not only impacts customer satisfaction but also limits opportunities for businesses to enhance sales and build trust.
Solution
Skin Match Technology introduces the Mobile Beauty Assistant: a cutting-edge digital product finder designed for salons, studios, and spas. This innovative tool uses AI-driven algorithms to deliver personalized product recommendations on the basis of a customer’s skin or hair type, sensitivities, and preferences (Skin Match, 2024). The following key features are described:
Interactive quiz
Customers activate the tool through a simple QR (quick response) code, answering questions about their skin or hair needs and preferences.
Personalized recommendations
Our proprietary algorithm analyzes product compositions from the salon’s inventory, offering a bespoke skincare or haircare routine tailored to each customer.
Real-time insights
Track best-selling products and emerging trends by location, enabling data-driven decisions.
Relevance
This solution bridges the gap between customer expectations for personalization and salons' ability to deliver. It transforms idle waiting or treatment time into an engaging and informative experience, enhancing customer satisfaction while driving additional revenue. By leveraging our extensive beauty industry data, we empower businesses to offer an unparaleled level of service. The integration of AI in tools such as this reflects ongoing advancements in the beauty industry, where AI-powered algorithms are redefining personalized skincare by providing tailored solutions on the basis of individual needs (Charllo, 2022).
Limitation
The Mobile Beauty Assistant focuses solely on cosmetics and does not offer medical solutions. In addition, the accuracy of recommendations depends on the quality and diversity of the dataset used by our algorithm. Although our database is comprehensive, it may not account for niche or newly launched products outside the network. Initial implementation also requires staff training to ensure that customers fully benefit from the tool.
SkinSpex: Smartphone-Based Imaging Solution
Context
Dermatologists and patients currently lack an objective, universal, cheap, easy way to document and track changes in chronic skin diseases (Afanasiev et al, 2019a). This is a problem because physicians cannot accurately assess dynamic change in disease severity or response to treatment between office visits, and patients cannot accurately capture and relay their disease and emotional burden at home. This leads to frustration among physicians and patients due to delay in diagnosis, inadequate control of disease burden, and inconsistency in care.
Solution
SkinSpex is a smartphone-based imaging solution that provides practical, accurate, and objective clinical-grade capture of skin conditions at the “point of disease” (usually at home) to enable better tracking of chronic skin disease. We utilize short video input to accurately reconstruct interactive 3-dimensional models of different skin conditions. The technology has analytic capabilities to accurately and objectively extract data from the life-like model to enable thorough assessment and aid diagnosis. Assessment of such reconstruction models is faster and more accurate than descriptive examinations, standard photographs, or original videos (Afanasiev et al, 2019b). This technology can be utilized during a standard office visit; it can enhance telemedicine care or even expand virtual clinical trials with remote monitoring of disease. This fast, scalable method is immediately deployable on smartphones and could be utilized to augment clinical decision making.
Limitations
Current limitations include the lack of larger datasets of full body images linked to other complex-associated features (QOL, associated symptoms, responses to treatments). Using SkinSpex technology, such a repository will be built and validated to train deep neural networks and AI algorithms for augmented clinical decision making.
Aneeq: Telehealth Solutions for Men’s Health
Context
Men in the Middle East often avoid traditional doctor visits, particularly for sensitive health issues such as hair loss, skincare, and sexual wellness. This hesitation stems from cultural stigmas and discomfort in discussing such concerns openly. These barriers contribute to delayed treatment and exacerbation of issues that could have been addressed earlier. Aneeq bridges this gap by offering a discreet and accessible telehealth platform that allows men to receive professional, prescription-based treatments without requiring in-person consultations (Alajlani and Clarke, 2013).
Solution
The aneeq.co journey begins with a tailored quiz where patients share their symptoms and medical history. On the basis of their responses, the platform recommends a personalized treatment plan. A licensed doctor validates the treatment on the backend, ensuring safety and efficacy. Once approved, the prescribed medication or product is delivered discreetly to the patient’s doorstep.
Aneeq’s telehealth platform is certified by Dubai Health Authority, ensuring that all treatments adhere to regulatory requirements for prescription medications and medical-grade products. This seamless integration of telehealth and regulatory compliance offers users a safe and effective alternative to traditional healthcare models. The platform reflects Dubai’s broader efforts to integrate digital technologies into health care, improving patient outcomes and accessibility to care (Middle East Health, 2024).
Limitations
Although Aneeq’s telehealth approach addresses significant barriers to care, it has its limitations. Certain cases may require in-person follow-ups to ensure optimal outcomes. It facilitates discreet access as opposed to a full diagnosis. In addition, navigating strict regulatory requirements can slow the pace of expansion into new markets. Finally, ensuring user adherence to treatment plans remains an ongoing challenge because sustained results depend on consistent engagement.
Aneeq represents a significant step forward in normalizing men’s health discussions and providing innovative, accessible care tailored to the unique needs of the Middle East.
Legit.Health: AI-Powered Dermatology Support
Context
Access to accurate dermatologic assessments is critical for timely and effective care, particularly in dermatology, where visual evaluations play a key role. Traditional methods often rely on manual scoring of skin conditions, which is time consuming and prone to variability. This challenge is amplified by growing patient volumes and long wait times for specialist appointments. Innovative digital health tools that integrate seamlessly with clinical workflows are essential to address these inefficiencies and enable hybrid care models that combine automated and human expertise (Afanasiev et al, 2019a).
Solution
Legit.Health offers an AI-powered diagnostic support tool designed to automate the severity scoring of over 300 skin conditions with scientifically validated accuracy. By providing automatic severity measures for tools such as PASI, Urticaria Activity Score over 7 days, Severity of Alopecia Tool, and more, Legit.Health reduces the time spent in office on assessments while improving reliability.
The platform is already trusted by healthcare providers in Europe, with successful deployments in public hospitals and integration with electronic health record systems. In 2023, Legit.Health launched the ASCORAD (Automatic SCORing Atopic Dermatitis), a ground-breaking solution for eczema management. This innovation has been instrumental in increasing efficiency in clinical trials and routine care (Afanasiev et al, 2019b).
Legit.Health’s application and API (application programming interface) are also integrated with systems used by dermatologists, enabling instant access to scores and reports. The company has garnered recognition through prestigious awards, including South Summit's Best Startup in Health and the EmprendeXXI Prize, further solidifying its role as a leader in digital dermatology. By combining AI innovation with clinical expertise, Legit.Health is reshaping dermatology care globally (Legit.Health, 2023).
Limitations
Current limitations include the need for larger datasets encompassing rare dermatologic conditions and patient-reported outcomes, such as QOL and response to treatments (Legit.Health, 2024). Addressing these gaps will further enhance the platform’s AI algorithms and strengthen its capabilities for augmented clinical decision making both in office and potentially in remote settings too.
Skintelligent: Skin Tech Company Specializing in AI Skin Analysis Software
Context
Within the field of dermatology, there is a gap between the frequency of clinical visits by patients and the frequency in which patients would like to self-monitor their skin, with at-home, mobile-centric software solutions. A patient that has received a diagnosis and is on a treatment regimen is evaluating their skin progress and results on a subjective basis but does not have tools that quantify and apply precision. This opens the need for a postdiagnostic monitoring layer to support the patient with data and measurement and to maintain compliance to the therapeutic regimen (Juyal et al, 2021).
Solution
Skintelligent developed a suite of AI-enabled skin imaging algorithms to enable skin measurement on mobile devices in an at-home setting. Our models aligned to validated scales for conditions such as acne and melasma. Each model was validated by a blind study versus dermatologists to ensure accuracy. The AI models are also used within clinical research to measure endpoints (Kololgi and Lahari, 2024).
Limitations
Data included images sourced from medical channels and dermatology clinics across 5 countries. There was good diversity in skin types in the training dataset. However, there were distinct gaps in Fitpatrick VI, and the models perform with lower accuracy on that subset. The software delivers strong, reliable results when the image quality and lighting conditions are good. Lower or degraded image quality or inconsistent lighting conditions can reduce the reliability of the result.
ilik Health: Teledermatology
Context
Accessing dermatologic care often presents significant challenges. Appointments with dermatologists are not only expensive but can also require long waiting times. On average, access to dermatologists by teledermatology is 1.9 days compared with 52 days for traditional dermatology visits (McKoy et al, 2004).
Simultaneously, the skincare industry tends to prioritize flashy packaging and persuasive marketing over substance, contributing to a flood of exaggerated claims and products with limited oversight. Although over-the-counter skincare products are easily accessible, they lack the clinical efficacy needed to address chronic skin concerns effectively because they require prescription-grade care. However, this level of personalized care is not always accessible to the average consumer.
Solution
ilik is a teledermatology platform designed to bridge this gap by delivering personalized prescription skincare in a convenient, efficient, and user-friendly manner. ilik focuses on treating common yet chronic skin conditions, including acne, hyperpigmentation, rosacea, and signs of aging, offering personalized prescription-grade care that is both effective and accessible.
The platform’s strength lies in its asynchronous approach offering hybrid care. Patients can complete a comprehensive online skin questionnaire at any time that suits their schedule. This process allows users to upload photographs and provide detailed information about their skin concerns without the hassle of traditional appointment scheduling.
What further sets ilik apart is its proprietary technology, developed in collaboration with dermatologists. This technology enables dermatologists to efficiently assess patient submissions, quickly provide accurate diagnoses, and prescribe tailored treatments. This streamlined approach lets dermatologists dedicate their efforts to crafting optimal treatment plans, minimizing the administrative burden that often comes with traditional care. The platform’s efficiency also helps to reduce costs, which are passed on to patients, ensuring an affordable yet professional dermatology solution (Vidal-Alaball et al, 2018).
Limitations
A potential limitation of the asynchronous teledermatology model is its reliance on high-quality patient-provided images and detailed input, coupled with the fact that some patients may lack trust in its ability to provide accurate diagnoses through pictures alone.
Conclusion
Although digital dermatology and AI-driven platforms enhance accessibility and efficiency, key challenges remain. Validation across diverse skin types is limited, particularly for darker tones (Fitzpatrick V–VI), affecting diagnostic accuracy. In addition, back-end validation requires dermatologist oversight, creating a bottleneck given workforce shortages. Not all conditions can be managed virtually, and some cases still require in-person evaluation, leading to potential delays. Image quality is another major limitation because low lighting, poor contrast, and focus issues can hinder AI and telehealth assessments. Future improvements should focus on expanding diverse datasets, streamlining validation, and integrating real-time image quality checks to enhance reliability and scalability. An overview of strengths and limitations are provided in Table 1. Table 2 highlights the key similarities, differences, and unique features of each of the start-ups.
Table 1.
Start-Ups' Key Strengths and Limitations
| Project | Key Strengths | Limitations |
|---|---|---|
| Skindr (online dermatology) | Fast, efficient online dermatology consultations reducing wait times | Limited for complex cases requiring in-person examination; challenges in AI triage |
| Skin Match (AI beauty recommendations) | AI-driven beauty recommendations improving personalization and user experience | No medical applications; dataset may lack niche or newly launched products |
| SkinSpex (3D skin imaging) | 3D skin imaging for accurate disease tracking and assessment | Lack of diverse datasets; it may create potential variability in patient image capture. |
| Aneeq (men’s telehealth) | Culturally tailored men’s telehealth platform improving access and discretion | Some cases require in-person follow-ups; regulatory challenges in new and emerging markets |
| Legit.Health (AI dermatology support) | AI-powered severity assessment tool that enhances precision and consistency while significantly reducing evaluation time, streamlining the decision-making process | Less effective for conditions requiring contextual analysis beyond visual evaluation |
| Skintelligent (AI skin analysis) | AI-based skin analysis enabling at-home skin tracking | Lower accuracy for darker skin tones; inconsistent image quality affecting reliability |
| ilik Health (teledermatology) | Asynchronous teledermatology improving accessibility and reducing wait times | Relies on high-quality patient-provided images |
Abbreviations: 3D, 3-dimensional; AI, artificial intelligence.
Table 2.
Comparative Analysis of Start-Ups: Key Similarities and Differences
| Project | Technology Type | Key Similarities | Key Differences |
|---|---|---|---|
| Skindr (online dermatology) | Teledermatology consultation platform | It is telemedicine based; it aims to improve dermatology care accessibility; reduces wait times | Direct consultation with dermatologists for quick online diagnoses to bypass the challenge of prolonged wait time |
| Skin Match (AI beauty recommendations) | AI-driven beauty recommendation engine | It uses AI for personalization and automation in the skincare and beauty domain | Primarily for beauty and skincare rather than medical dermatology |
| SkinSpex (3D skin imaging) | 3D imaging technology for skin disease tracking | It relies on image-based assessment for dermatologic and cosmetic insights. | Uses 3D imaging for disease severity monitoring and not static images |
| Aneeq (men’s telehealth) | Telehealth platform for men’s dermatologic concerns | It is designed for remote access, minimizing barriers to care for men’s health advancement. | Focusses on men’s health, addressing hair loss, skincare, and related concerns |
| Legit.Health (AI dermatology Support) | AI-powered medical device for dermatologic diagnosis support and severity assessment | It is an AI-driven automation enhances efficiency, reducing workload for specialists. | AI-driven severity assessment for dermatologic conditions, paired with diagnostic support for over 323 skin conditions |
| Skintelligent (AI skin analysis) | AI-based at-home skin analysis software | It focusses on improving dermatologic diagnosis, monitoring, and treatment outcomes. | Provides at-home AI-powered skin analysis, reducing dependency on in-person visits |
| ilik Health (teledermatology) | Teledermatology consultation model | It supports asynchronous consultations for user convenience and efficiency. | Combines dermatologist validation and personalized treatments |
Abbreviations: 3D, 3-dimensional; AI, artificial intelligence.
By integrating cutting-edge digital technologies, these entrepreneurs aim to revolutionize dermatologic care, making it more accessible, proactive, predictive, and patient centered. However, numerous challenges remain.
The most critical challenge is creating large, diverse, and high-quality datasets that truly represent the breadth of patient demographics and conditions. These datasets are essential for developing robust, unbiased AI systems capable of delivering transformative improvements in healthcare outcomes for all. Equally important is ensuring that these solutions undergo rigorous testing in clinical settings before widespread implementation.
Another challenge is ensuring that dermatologists and skin-trained healthcare professionals retain their central role in patient care, preserving the human touch and expert judgment in an increasingly digital landscape (du Crest et al, 2024). At the same time, there is a critical need to address backend validation processes and anticipate potential bottlenecks arising from the shortage of dermatologists, which could hinder the scalability and effectiveness of these digital solutions.
Beyond industry-led product and service innovation, the ongoing digital advancements driven by entrepreneurs emphasize the importance of blending technology with daily dermatologic care. Looking ahead, the synergy between basic, translational, and clinical dermatologic researchers, clinicians, and digital innovators promises ground-breaking progress, reshaping the landscape of dermatologic, esthetic, and skincare science for years to come.
Addressing these challenges and fostering this collaboration are essential for successfully tackling current issues, anticipating future needs, and ensuring that skin health care evolves alongside digital technological advancements.
ORCIDs
Dominique du Crest: http://orcid.org/0000-0002-2496-3018
Annelies Avermaete: http://orcid.org/0009-0006-0169-0615
Estella Benz: http://orcid.org/0009-0002-7821-6509
Olga Afanasiev: http://orcid.org/0000-0002-6358-6163
Hassan Galadari: http://orcid.org/0000-0001-8223-2769
Alfonso Medela: http://orcid.org/0000-0001-5859-5439
Eleanor Jones: http://orcid.org/0009-0004-2617-4938
Dina Sidani: http://orcid.org/0009-0006-8231-8830
Alexander Zink: http://orcid.org/0000-0001-9313-6588
Merete Hædersdal: http://orcid.org/0000-0003-1250-2035
Lilit Garibyan: http://orcid.org/0000-0002-9266-0887
Conflict of Interest
DdC is an employee of SkinAid SAS and receives salaries from the company. AA is an employee of Skindr and receives salaries from the company. EB holds share of Skin Match Technology. HG holds share of Aneeq. AM holds shares of AI Labs Group SL. EJ is an employee of Codex Labs, receives salaries from, and holds shares in the company. DS holds shares of ilik Health. The remaining authors state no conflict of interest.
Acknowledgments
The Skin & Digital Summit thanks its scientific partners in 2024: Advancing Innovation in Dermatology, the International Master Course on Aging Science, the International Federation of Psoriasis Associations, the International Alliance of Dermatology Patient Organizations, the Master of Aesthetics, and Magic Wand Initiative. This article was funded by SkinAid SAS.
Declaration of Generative Artificial Intelligence (AI) or Large Language Models (LLMS)
The author(s) did not use AI/LLM in any part of the research process and/or manuscript preparation.
Accepted manuscript published online 10 April 2025; corrected proof published online 14 May 2025
Footnotes
Cite this article as: JID Innovations 2025.100371
References
- Afanasiev O., Tabata M., Narla A., Scott G., Ko J.M. SkinSpecs: a mobile solution that addresses an unmet need for tracking chronic skin diseases in the office and at home. SKIN. 2019;5:309–320. [Google Scholar]
- Afanasiev O.K., Tabata T., Ko D. The need for objective and remote tracking of chronic skin diseases. SKIN. 2019;3:405–409. [Google Scholar]
- Alajlani M., Clarke M. Telemedicine and the battle of change: a tale of two regions. Health Policy Technol. 2013;2:229–241. [Google Scholar]
- Charllo B. The role of AI in driving personalization in cosmetics. J Artif Intell Mach Learn Data Sci. 2022;5:45–58. [Google Scholar]
- du Crest D., Garibyan L., Hædersdal M., Zink A., Madhumita M., Harth Y., et al. Skin & digital–the 2022 startups. Dermatologie. 2023;74:899–903. doi: 10.1007/s00105-023-05204-8. [DOI] [PubMed] [Google Scholar]
- du Crest D., Madhumita M., Enbiale W., Zink A., Papier A., Matewa G., et al. Skin and digital–the 2024 narrative. 2024. https://www.mcpdigitalhealth.org/article/S2949-7612(24)00043-9/fulltext (accessed March 20, 2025) [DOI] [PMC free article] [PubMed]
- du Crest D., Wustrow P., Worsley O., Zink A., Hædersdal M., Garibyan L., et al. Skin & digital: the 2023 startups/innovators. JID Innov. 2023;5 doi: 10.1016/j.xjidi.2024.100316. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Inkwood Research Beauty and personal care market. Inkwood Research. https://www.inkwoodresearch.com/reports/beauty-and-personal-care-market/
- Juyal S., Sharma S., Shukla A.S. Smart skin health monitoring using AI-enabled cloud-based IoT. Mater Today Proc. 2021;46:10539–10545. [Google Scholar]
- Kololgi SP, Lahari CS. Harnessing the power of artificial intelligence in dermatology: a comprehensive commentary. Indian J Dermatol. 2024;68:678–681. doi: 10.4103/ijd.ijd_581_23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lambert J., Lambert J., Roegies K., Nikkels A., Garmyn M., Snauwaert J., et al. The doctor will see you now, in 4 months: a Belgian perspective on waiting times for dermatologic care. J Eur Acad Dermatol Venereol. 2025;39:e204–e205. doi: 10.1111/jdv.20161. [DOI] [PubMed] [Google Scholar]
- Legit. Health Enhancing dermatologic care through AI-powered tools. Journal of Digital Health Innovation. 2024 https://legit.health [Google Scholar]
- McKoy K.C., DiGregorio S., Stira L. Asynchronous teledermatology in an urban primary care practice. Telemed J E Health. 2004;10 S–70–80. [PubMed] [Google Scholar]
- Mintel 2023 global beauty & personal care trends. 2023. https://www.mintel.com/insights/events/2023-global-beauty-personal-care-trends/
- Middle East Health Transforming healthcare in Dubai: the role of digital technology in improving patient outcomes. 2024. https://middleeasthealth.com/medical-specialty-features/health-information-technology/transforming-healthcare-in-dubai-the-role-of-digital-technology-in-improving-patient-outcomes/
- Skin match technology AG. Internal data; 2024. [Google Scholar]
- Skindr 2024. https://www.skindr.com/ (accessed December 16, 2024)
- Vidal-Alaball J., Garcia Domingo J.L., Garcia Cuyàs F., Mendioroz Peña J., Flores Mateo G., Deniel Rosanas J., et al. A cost savings analysis of asynchronous teledermatology compared to face-to-face dermatology in Catalonia. BMC Health Serv Res. 2018;18:650. doi: 10.1186/s12913-018-3464-4. [DOI] [PMC free article] [PubMed] [Google Scholar]