AI/ML Consulting

I help organizations go from AI curiosity to production value. Whether you need a strategic assessment, a working prototype, or a production system, I bring the rare combination of academic depth and engineering pragmatism.

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What I Do

Knowledge Architecture & Semantic Systems Ontology design, taxonomy development, and knowledge graph construction that give your organization a structured foundation for AI. From entity modeling to graph-based analytics, I help teams move beyond flat data toward connected, semantic representations that compound in value.

LLM & Generative AI System Design Architecture and implementation of RAG pipelines, agent systems, and LLM-powered workflows — including graph-enhanced retrieval that grounds generation in structured domain knowledge rather than raw text alone.

Custom ML Model Development End-to-end model lifecycle: problem framing, data strategy, training, evaluation, and deployment. Specializing in NLP, graph neural networks, information retrieval, and classification.

Rapid Prototyping & POC Development Narrow vertical-slice proofs of concept delivered on short timelines. Get a working demonstration in front of stakeholders fast, then iterate.

Technical Training & Workshops Making ML/AI accessible to non-technical teams. Drawing on years of university teaching (PhD-level ML, Python, GIS) and industry presentations at FactSet Developer Days and with defense partners.


How I Work

Many clients come with only a basic understanding of what ML can do for them. I start by understanding your actual problem — not the technology you think you need. From there:

  1. Problem Framing — Define what success looks like in measurable terms
  2. Feasibility Assessment — Honest evaluation of what ML can and cannot do for your use case
  3. Rapid Prototype — Working demonstration, typically in 2-4 weeks
  4. Production Path — Architecture, deployment, and handoff to your team
ML workflow diagram

Who I Work With

  • Startups needing ML capabilities without a full ML team
  • NGOs and research organizations needing data science and geospatial expertise
  • Enterprise teams seeking external perspective on AI strategy
  • Political campaigns needing data-driven analysis
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