Austin, TX · Remote engagements welcome
Most AI initiatives fail not because of bad models, but because the knowledge underneath was never made legible — to the machines processing it, or to the humans acting on it. We close that gap.
Sensemaking is the step most AI projects skip. You can have clean data, a fine-tuned model, and a beautiful dashboard — and still build something nobody trusts or uses, because the representation never matched how the people downstream actually think.
AI strategy, RAG systems, knowledge graphs, and ML projects from problem definition through production deployment — with full knowledge transfer so your team owns the result.
AI strategy sprints · RAG architecture · Knowledge graph development · ML pipeline deployment
Data-for-AI readiness training for teams and individuals preparing their knowledge, documentation, and data for AI adoption. The best model in the world can't fix upstream chaos.
Data readiness assessments · Documentation strategy · Team workshops · Individual coaching
Custom AI assistants trained on your expertise and deployed to your domain. Your writing, projects, and professional narrative — made conversational and citable.
Domain-specific chatbots · Domain-specific RAG · Custom knowledge bases · Production hosting
A PhD dissertation (400+ citations) on how humans construct meaning from visual information — applied to every system we design.
From fuzzy requirements through architecture, implementation, and deployment. Present to a C-suite or debug the pipeline — same person.
Shipped production systems across NLP, computer vision, knowledge graphs, and LLM applications. CDMP-certified in data management.
Cognitive Scientist · AI/ML Engineer · Builder
My MIT dissertation showed that humans don't passively receive data — we actively construct meaning from it, using everything we already know before we're even conscious of looking. That finding shapes every system I design.
I'm a consultant who codes, an engineer who communicates, and a strategist who ships. I take projects from fuzzy requirements through production — and I can present the results to leadership or debug the pipeline myself.
I built an AI trained on my work, writing, and methodology. Ask it anything about my approach, projects, or frameworks — it answers in my voice, with citations.