Projects
Each project is an AI agent that shows a reusable product capability — financial reasoning, forecasting, discovery, governance. A card gets a screenshot and a link only once it’s real.
An agent that underwrites an investment end to end — pulling multiple data sources, reasoning across them, and returning an explainable recommendation with its supporting numbers and risks. First example implementation: residential real estate, where it scores a listing and shows the why.
Optimizes prices against forecast demand and business constraints, and explains each recommendation so a human can trust and override it.
Automates discovery research — synthesizes scattered customer signal into ranked, evidence-backed product opportunities.
Runs the repetitive product-ops workflows and keeps team knowledge searchable and current, so the team spends its time on judgment, not upkeep.
Monitors AI systems for risk and turns the signals into executive-ready governance reporting — the responsible-AI layer that lets enterprises ship with confidence.
An AI-guided coaching app that pairs a large library of techniques with adaptive, personalized sessions and an immersive 3D avatar. I was the first engineer hired, then built the team — and learned C# and Unity to code the first avatar animation myself. Owned architecture, biofeedback, security, and privacy.
A digital-health platform (later public, TSXV: CRBK). I led the data and ML work: designed a systematic literature-search process to collect health-risk factors and built a relative-risk model to predict disease risk — the Health Risk Assessment that became the company's core IP — plus an ROI calculator for insurers.