Understanding business, then building the systems that run it better.
I work at the intersection of business operations, financial analysis, and artificial intelligence — reading how a business actually performs, then building the models, tools, and AI-powered systems that turn that understanding into better decisions.
How I think about systems and decisions.
My work combines structure, curiosity, and implementation. I am interested in how data, systems, and artificial intelligence can be shaped into tools that are not only technically sound, but genuinely useful in real operating environments.
What I care about
I am drawn to ideas that connect intelligence with action: systems that make work clearer, decisions more grounded, and organizations more capable.
How I think
I value simplicity, depth, and relevance. I prefer solutions that are elegant, understandable, and shaped around real human and business needs.
Business, financial, and operational systems.
I work closely with real business operations — analyzing financial and operational performance, then building the models and systems that turn that understanding into better decisions.
Business Intelligence & Financial-Operational Systems
Six connected models built for a multi-location hospitality business — spanning financial projection, cost control, inventory, pricing, purchasing, and workforce planning.
Financial & Operational Analysis
Reading business performance through revenue, cost, labor, and inventory data to find where the real leverage is.
Analytics & Forecasting
Turning raw operational data into structured models — projections, variance tracking, and decision-support tools grounded in business context.
Applied Artificial Intelligence
Building AI-powered products, agents, and automations that connect directly to real business and operational problems.
Product Thinking
Designing tools people actually use — with attention to adoption, usefulness, and long-term value, not just technical correctness.
Selected areas of work.
Practical intelligence for business environments
Designing systems that use AI to support operational understanding, process improvement, and more thoughtful day-to-day decision-making.
Data-driven structure and insight
Building analytical approaches that translate complexity into clear, usable information for teams, leaders, and organizations.
Systems with real-world usefulness
Exploring how intelligent products can move from concept to practical implementation with clarity, usefulness, and focus.