About the client
The client is a leading healthtech company focused on early skin cancer detection through its AI-powered mobile application. The app allows users to assess the risk level of moles and skin spots with clinically validated accuracy, achieving over 90% sensitivity in identifying potential skin cancers. Trusted by over 3 million users worldwide, the client partners with insurers, NGOs, and global brands to expand access.
Country
Netherlands
Industry
Healthtech
Services Used
Understanding the vision
Skin cancer is common but highly treatable if caught early. The client’s app allowed users to submit photos of their moles or skin abnormalities for dermatologist review, but growing demand exposed limitations in speed and scalability.
The existing application relied entirely on manual dermatological review, leading to delays in diagnosis, scalability issues, and limitations in delivering immediate value to users concerned about potential skin cancer symptoms. To fulfill its mission of enabling early skin cancer detection at scale, the client envisioned restructuring its platform by integrating an AI model, capable of analyzing user-submitted skin images and detecting potential signs of skin cancer in real time. This would help deliver faster, smarter, and more globally accessible skin health assessments.
In order to revamp their platform and meet the rising demand for faster and scalable skin assessments, the client turned to Daffodil Software. With proven expertise in AI development in the healthcare industry, Daffodil was chosen to lead the platform modernization.
The key requirements were:
Embedding a clinically validated AI models into the app to assess the risk level of skin lesions in real time in order to provide users with instant feedback on potential skin cancer concerns.
Completely restructuring the legacy application to adopt a modular and scalable architecture that supports rapid innovation and secure integrations.
Implementing data protection measures to comply with GDPR and healthcare security standards, with encrypted storage and consent-driven data usage.
Supporting global expansion through multilingual capabilities, localized content, and adaptability to different regulatory landscapes.
Adding new features such as location-based UV Index alerts, histopathology report uploads for enhanced analysis, subscription-based access to premium features, etc.
Modernizing an AI-driven skin cancer detection app
Team Daffodil began the project by working closely with the client’s product teams to understand their goals of improving diagnostic speed, enabling global reach, and integrating AI into the core of their skin health platform. Our collaborative sessions helped us align on key priorities: restructuring the app’s architecture, embedding AI seamlessly into user workflows, and ensuring compliance with healthcare data regulations.
To modernize the platform, we rebuilt the iOS application in Swift, enabling better performance, improved UI responsiveness, and future scalability. On the Android side, we refactored the legacy codebase from Java to Kotlin, leveraging its modern syntax and interoperability to streamline development and maintenance.
We restructured the backend into a cloud-ready, modular architecture, making the system more scalable, easier to maintain, and capable of integrating AI workflows. This new setup enabled us to plug in the AI model with minimal disruption to the overall flow, supporting real-time lesion analysis and rapid feedback loops between users and clinical reviewers.
To support secure growth across regions, we implemented GDPR-compliant data workflows in line with Dutch data protection laws, ensuring encrypted data handling and user-consent management without disrupting usability.
By modernizing the tech stack and embedding AI at the core, we helped the client evolve into a smart, scalable platform for early skin cancer detection.
The key features we included were:
We incorporated AI-based mole detection to enable the app to scan and assess images of skin lesions uploaded by users. The clinically validated AI model was embedded into the workflow to provide real-time risk evaluations, reducing reliance on manual dermatological reviews. This allowed the system to deliver instant, data-driven feedback to users, significantly improving diagnostic speed and supporting the client’s goal of scalable early skin cancer detection.
To promote proactive skin care, we introduced a location-based UV Index feature that alerts users about daily sun exposure risks. This empowers individuals to make informed decisions about sun protection, reducing their chances of developing skin conditions over time. By leveraging geolocation and real-time weather APIs, the app delivers personalized, region-specific UV alerts, thus aligning with the client’s mission of preventive health.
We incorporated a subscription-based model that limits the number of image uploads for free users while offering expanded access to paid subscribers. This feature allows users to assess a limited number of skin lesions each month at no cost, with the option to upgrade for unlimited or higher-volume usage. It enables the client to balance accessibility with sustainability, ensuring the platform remains free for casual users while generating revenue from high-frequency users or medical professionals.
We incorporated a secure messaging feature to facilitate communication between users and clinical reviewers or support teams. This was designed to help users receive clarification on their scan results, understand next steps, and ask follow-up questions within the app. The messaging system was built to align with healthcare compliance requirements while maintaining usability, ultimately improving user interaction with the platform.
Tangible results from the platform overhaul
The new AI-powered skin health assessment platform enabled the client to drastically improve diagnostic speed and service scalability. Real-time image analysis replaced manual review bottlenecks, allowing users to receive instant, clinically reliable feedback. The updated architecture supported seamless AI integration and efficient handling of growing user traffic across regions. As a result, the client expanded its global footprint, improved user satisfaction, and strengthened its position as a trusted provider in digital dermatology. The platform has already delivered millions of faster, data-backed skin checks, directly supporting the client’s mission of early skin cancer detection at scale.
3M+
Users Worldwide
5M+
Skin Checks till date
90%
Sensitivity in Identifying Potential Skin Cancers
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