HCDS Architect. Agentic AI & Civic Tech.
A quantitative analysis of Toronto’s shelter system using Python & Open Data. This audit revealed critical saturation points in specific sectors (e.g., Women & Youth services hitting 99% capacity) and visualized systemic gaps to support data-driven policy advocacy.
An advanced Agentic AI architecture moving beyond stateless RAG. Built with LangGraph, this system maintains "Cognitive State" to handle multi-turn reasoning and crisis management, simulating a proactive teammate rather than a reactive chatbot.
A novel predictive model exploring "Economic Empathy" in climate algorithms. This project analyzes real-estate market fluctuations as leading indicators for forest fire risks, bridging the gap between financial data and environmental safety.
2026-01-01
Why "Stateless" RAG fails in crisis scenarios—and a technical blueprint for building Cognitive State using LangGraph. A shift from reactive bots to proactive agentic workflows.
2025-12-08
A technical proposal for predicting forest fires using Real-Estate Market signals instead of just thermal sensors. How economic data can act as a leading indicator for environmental disasters.