AI automation and business-systems builder. I turn real operating workflows into reliable, repeatable software — mostly agentic AI systems in Python.
Law Engine A structured legal-intelligence and learning platform — real provenance-tracked statutory text (UCC Articles 1, 2, 3, and 9, Virginia enactment), a deterministic legal-reasoning engine, and an interactive TypeScript/Next.js/React study app with real interactive scenarios. Public, Apache-2.0.
Company Intelligence Pipeline A real, end-to-end data-engineering pipeline — SEC EDGAR financial disclosures, real provenance, a normalized relational schema, automated data-quality validation, and advanced SQL analytics for 5 public companies. Public, Apache-2.0.
Enterprise Agent Lab A real MCP server plus two independent agent-orchestration implementations (plain Python and LangGraph) around the same deny-by-default, human-approval-gated workflow.
AI-Native Content Operating System A content-systems reference model — discovery, production, quality gates, distribution, and a checkable refresh-priority formula.
GhostOS A private, ongoing agentic operating system I build and run daily — Python, deterministic decision engines, real API integrations (CRM, ads, marketplaces), and a real automated test suite in the thousands. Source is private; the four repos above are public products/extractions built on the same platform.
Sixteen-plus years across enterprise storage hardware and firmware/software validation; technical support; account management; and sales engineering and team leadership; and real estate transaction coordination, sales, and investing; — now applied to building the AI automation that replaces the manual versions of that same work.
Agentic AI, MCP, LangGraph, and business-workflow automation.