Projects
Power BI engineering, agentic AI in practice, and public-good decision support. Each project shows its source, scope, and stage.
Inspectable repositories for Power BI testing and maintainable delivery.
powerbi_demo_PBIPxGHCopilot
Automated DAX measure testing built on PBIP, Python, and AI-assisted tooling, designed to catch calculation risk before deployment.
Validation-first BI engineering: systematic DAX risk detection, repeatable test coverage, and CI-ready semantic model workflows.
Applied AI built under event constraints, with the prototype scope kept visible.
modellismz/OpenSkillTrace
Sea x OpenAI Codex Hackathon build: an AgentOps harness for tracing agent runs, routing fallbacks, checking eval and policy signals, and keeping approval and audit controls visible.
Forward-deployed AI is not just prompt output. The useful work is the control layer around tools, data, fallbacks, and human decision gates.
disaster-dashboard-webapp-repo
Disaster-response dashboard copilot shaped around the Asia Pacific AI Skills Jam: profile fragmented CSV and Excel files, surface evidence gaps, recommend dashboard views, and export a reviewable decision handoff.
Applied AI with BI discipline: start from messy operational data, keep deterministic checks visible, use AI only where it improves reasoning, and leave decision ownership with humans.
Internal engineering templates and experiments. Repository access remains private.
PBI_Agent
A deterministic PBIP and PBIR engineering template that enforces validation gates, consistent folder structure, and governance-ready defaults.
Structured engineering habits that transfer across projects: repeatable repository design, clear validation checkpoints, and governance-aware BI delivery.
Repository access is private.
A2A
A multi-agent framework exploring AI-assisted orchestration across Azure, Power BI, and Databricks BI workflows.
Early-stage but grounded: tests whether multi-agent patterns can reduce manual coordination in real BI delivery pipelines.
Repository access is private.
Static reference pages showing decision context, model plans, source checks, and validation notes.
A public-data Power BI reference demo scaffold showing how airline reliability data can move from decision context to source-aware actions, with semantic model proof and validation gates visible before any iframe is published.
Contact
Start with the reporting or data problem, the current constraints, and the part of the workflow that needs better structure.