Elevator Maintenance Flow
AI-powered predictive maintenance for vertical transport
End-to-end PoC exploring how AI and real-time IoT data can transform elevator maintenance from reactive to predictive. A risk model surfaces the units most likely to fail, and an on-demand voice briefing — generated with Amazon Bedrock and read aloud in the browser — turns each unit's risk data into an actionable summary for technicians, helping Operations Managers cut downtime and optimise their teams. Built using Spec-Driven Development (SDD) with Claude Code — a deliberate step into the Product Maker space — with a React + Vite frontend and FastAPI + PostgreSQL backend, deployed to AWS via a GitHub Actions CI/CD pipeline (Docker, nginx, TLS).