Adopting AI responsibly, at the scale where trust is non-negotiable.

The executive operating layer that runs many AI products as one governed portfolio, not another single-purpose app. It integrates the other three projects live, reading each app's real snapshot endpoint through typed adapters, and is registry-driven. A 7-stage governance state machine drives a live audit trail across the Responsible AI Center, Human Approval Center, and a risk heatmap, under a "no seed, ever" principle: every figure is live or honestly marked "Not reported."

A production-grade RAG assistant built to demonstrate Responsible AI at production standards: a deterministic LLM-as-Judge evaluation harness, a local NLI-entailment filter that drops unsupported claims, an answerability gate that refuses rather than fabricates, and page-level clickable citations.

An autonomous agent that converts live Canadian public data (Statistics Canada, Bank of Canada, CMHC) into decision-ready retail-banking strategy briefs, built on the Model Context Protocol. Responsible-AI guardrails are first-class: no forecasts, no regulated advice, automatic low-confidence flagging, and source traceability on every figure.

A deployed, full-stack self-assessment that helps teams gauge their AI-native maturity, with shared persistence and a team view. Demonstrates product lifecycle ownership from concept through live deployment and iteration across three released versions.