Where I help
Four areas, one discipline: govern the structure first, and everything built on top — human or agent — inherits order instead of chaos.
Enterprise Data Architecture & Strategy
Canonical/3NF data modeling, master data management, entity resolution, and "Rosetta Stone" enterprise information hubs. I turn disjointed transactional systems into a single, governed source of truth that both people and applications can trust — the foundational discipline behind everything else I do.
AI Governance & Agentic Systems
Governance frameworks for AI itself: schema, RBAC, lineage, and immutable audit applied to agent skills, decisions, and patterns — not just production data. Responsible AI policy, token economics and AI FinOps, and architecture for production agentic workflows (Claude Code, Microsoft Copilot, multi-agent orchestration) that deploy safely at enterprise scale.
M&A Technology Integration
Post-acquisition systems rationalization, technology due diligence, and architecture alignment. I've led this from both sides — architecting target-state systems for acquirers and running the actual merged-environment migration — across Fortune 100 and mid-market engagements alike.
Regulated-Industry Data Platforms
Data architecture built to withstand a regulator's questions, not just pass a demo. Deep experience in healthcare payer/provider (HIPAA), financial services (SOX), and pharmaceutical/biotech environments — governance as a foundation, not an afterthought.
How engagements typically start
A conversation, not a proposal template. Tell me what's actually broken or what you're trying to build, and we'll figure out from there whether it's a fit.