About me

I build software that turns messy work into useful systems.

I am a software developer and data engineer with more than a decade in corporate IT environments, with a practical focus on master data, automation, internal tools, and AI-assisted workflows. I like work that lives close to real operations: the places where data quality, workflow design, security, and user trust all have to survive contact with day-to-day use. You can find more professional context on LinkedIn.

Lately that has meant building local-first research systems, document ingestion and audit tools, AI gateway patterns, product prototypes, and fantasy football analysis workflows that combine public data, private notes, and repeatable decision support.

What I build

Code, data, and judgment in the same room.

The through-line is making complicated information easier to inspect, act on, and improve over time.

Data systems

Operational data that compounds

Data models, pipelines, quality checks, and local analytics layers for work that needs reliable context instead of one-off exports.

AI workflows

Practical AI around real constraints

Document extraction, audit support, local model gateways, agentic review loops, and human-in-the-loop systems that keep sensitive data controlled.

Products

Tools people can actually use

Web and mobile app surfaces, internal portals, dashboards, workflow tools, and experiments that turn ideas into working software.

This site

A public workbench.

This site is a code-first home for writing, projects, fantasy football analysis, and small interactive tools. Some work can be shown directly. Some work involves private repos, client-like contexts, or sensitive documents, so I describe those projects by the type of problem solved rather than by exposing names, data, or implementation details that should stay private.

My bias is toward useful, inspectable artifacts: clear notes, runnable tools, durable research, and software that can be maintained by humans and AI agents working together.