I’m building a mobile-first application that takes raw health data from users—think wearables, lab results, daily logs—and runs it through an AI engine focused on data analysis and predictions. The core of the job is to design, build, and deploy the end-to-end solution: secure data intake, a clean user dashboard, and a prediction module that surfaces trends, risks, and actionable insights in real time. Because the app’s competitive edge is the AI itself, I expect you to leverage modern AI development tools (AutoML, pretrained models, or similar) so the build is faster and my overall cost stays sensible. Your workflow should make smart use of automation for model selection, tuning, and deployment—no hand-coding every model from scratch unless absolutely necessary. Key deliverables • A responsive Android/iOS app (React Native or Flutter preferred, but open to suggestions) • A cloud-hosted AI pipeline that processes health data and returns predictions via API • Basic analytics dashboard showing trends, confidence scores, and explanation snippets • Secure user authentication and HIPAA-aware data handling (encryption in transit and at rest) • Documentation: system architecture, model provenance, setup scripts, and a quick-start guide for future enhancements I’ll provide sample anonymized datasets for initial training and testing. Accuracy, performance, and maintainability will be measured against industry norms for health-focused predictive apps; we’ll agree on specific acceptance metrics before sprint one kicks off. If you have a portfolio of AI-powered apps—especially those centered on health data analysis and predictions—I’d love to see it when you respond.