Cura Healthcare

Context

• Cura is a Saudi telemedicine platform reporting 3,000+ monthly consultations.
• The work needed to support patient and doctor journeys across web and mobile, while allowing shared features to evolve efficiently.

What I built

New Flutter doctor app, built end to end with AI-assisted development

Built the replacement doctor app in Flutter from the ground up using AI-assisted development, including mobile navigation, notifications, permissions, and integration with the web experience. I also delivered major doctor-facing features in Next.js, with shared web functionality supporting both patient and doctor apps.

AI-assisted Flutter delivery

Flutter is outside my core stack, so I built the doctor app with AI-assisted development using Claude Code and Codex. I owned the architecture, requirements, and integration with our existing Next.js platform, while the AI tools generated much of the Flutter code. I reviewed, tested, and debugged everything before release. This let a web-focused team ship a production mobile app without hiring a dedicated Flutter developer.

Patient journeys, integrations, and real-time chat

Built core patient journeys across JWT-based authentication, search, profiles, consultation booking, and checkout, including payment-service integration. Co-developed insurance integrations and built real-time patient–doctor chat, with further contributions to lab-test ordering, e-prescriptions, and voice and video calling.

Platform maintenance and performance

Contributed to the Next.js modernization and improved rendering, assets, and data loading through caching, lazy loading, and request optimization. Reduced startup time for the mobile web experience, with before-and-after measurements, and contributed localization, SEO, and journey analytics.

Outcome

• ~50%reduced development time from shared web features
• ~30%improvement in measured web-performance metrics
• ~35%reduction in average data-loading time
• ~30–40%reduction in mobile web startup time

• The development-time reduction is an approximate internal estimate; performance figures are approximate before-and-after measurements covering different scopes and may overlap.
• Shared web features reduced duplicate implementation across the patient and doctor apps. Web-content updates could ship independently of native app releases.