Intelligent systems in practice
Projects & systems
AI/ML applications, LLM observability, and cloud-native platforms I build, evaluate, and deploy—where model quality, safety, and production infrastructure are designed together from the start.
Production-oriented observability for AI apps: OpenAI-compatible proxy, request tracing, usage and cost analytics, threshold alerts, and incident-style triage. Built for teams who need to answer what broke, for whom, and at what cost when models, guardrails, or traffic patterns change. FastAPI backend, React + Vite frontend, Apache 2.0.
Agentic web app for sinkhole risk in the Winter Park, Florida karst district—XGBoost susceptibility plus Gemini for explanation, monitoring, and alert drafting. A case study in high-stakes decision support where model outputs must be contextualized, monitored, and tied to real-world sensors—not just a one-off prediction.
DayFlowAI merges calendar data, weather, and a lightweight assistant into a serverless dashboard. Built as part of the AWS re/Start program with a team of collaborators and deployed on AWS Amplify and managed cloud services.