MLNavigator

Donella Dawn Cohen and I started MLNavigator to build local-first AI for regulated environments: governance, privacy, and deployment you can still review after it runs. The teams operating under the strictest constraints had the fewest real options, which is the gap the company works in.

Before MLNavigator

Before ML research, I worked across defense, AV engineering, and product design: Bombardier Defense, CTI, and Lazerworx. I studied Product Design and Manufacturing Engineering at Wichita State.

Aerospace, defense, and manufacturing can use AI only when the boundaries stay explicit. Compliance is the floor; unexplained behavior is not a feature.

adapterOS

adapterOS is the research effort at the center of that work: local-first AI and high-assurance workflows for regulated environments. NSF I-Corps cohort; Kansas ACCEL grant recipient.

What I look for

Software that can be examined after the fact, and governed without guessing why it did what it did.

How I work

I apply systems engineering to local-first AI. Durable software, named boundaries, and a deploy path that still makes sense when someone else has to answer for it. Get in touch.