The engineer behind the practice
MOX Consulting is not an agency. It's an engineering practice — built on over a decade of solving real operational problems at production scale, now applied to the organizations that need it most.
I spent over 12 years building and maintaining production data systems in semiconductor manufacturing — the kind of environment where bad data costs hundreds of thousands of dollars and broken integrations shut down assembly lines. That experience taught me what it actually means to engineer reliable systems, not just configure tools.
My background spans electronics and mechatronics engineering, embedded systems, software development (C#, Python, and more), IoT, and AI agent architecture. I've worked at every layer of a technical stack — from microcontrollers and hardware interfaces to enterprise data pipelines and machine learning integrations.
MOX exists because I kept seeing small businesses, churches, and schools struggling with the exact same operational problems that enterprise companies solve with huge IT budgets — but nobody was bringing engineering-grade solutions to organizations at that scale. So I built a practice to do exactly that.
Every system we build is designed to be owned, maintained, and understood by the people using it. No vendor lock-in. No black boxes. No billing-by-the-hour surprises. Just reliable systems, documented and delivered.
Built on real engineering — not buzzwords
The skills behind MOX aren't consulting frameworks. They're production-tested engineering disciplines applied to business operations.
Systems & Embedded Engineering
Electronics, mechatronics, microcontrollers (ESP32, Arduino, Raspberry Pi), IoT architecture, and hardware-software integration. The discipline of making systems reliable at the hardware level carries directly into software and data design.
Software & Data Engineering
C#, Python, MicroPython, SQL, API design, and ETL pipelines. From building Windows desktop applications to cloud-based data pipelines and AI agent architectures — full-stack engineering applied to operational problems.
AI & Automation Architecture
LLM integration, AI agent design, workflow automation, and intelligent document processing. Applied AI that connects to real business data and produces measurable operational outcomes — not demos and experiments.
How we think about every engagement
These aren't talking points. They're the principles that govern every system we design and every recommendation we make.
Clean Data First
No automation. No AI. Nothing until the data foundation is clean, structured, and reliable. Building on dirty data creates confident misinformation.
You Own Your Data
Every system we design prioritizes your ability to export, migrate, and control your own data. We evaluate every tool against its API access and data portability before recommending it.
Scope Before Code
We document exactly what's being built before writing a line of code. Fixed-scope engagements mean no billing surprises and clear mutual expectations from day one.
Documentation is the Product
Every system we build comes with runbooks your non-technical team can follow. If it isn't documented, we didn't finish the job.
Maintainability Over Cleverness
A system that works reliably for three years beats an elegant one that breaks in six months. We choose boring, proven patterns over impressive complexity.
Honest Assessment Always
If your organization isn't ready for automation, we'll tell you. The free audit is designed to produce an honest picture — not a sales funnel for implementation work.