About Me

I bridge the gap between complex data and high-stakes decision-making. With a decade of experience in sustainability and humanitarian data science, I now build the “logic layer” for the next generation of AI—the ontologies, semantic models, and knowledge graphs that turn raw information into machine-readable reasoning.

What I Do

I am a Knowledge Engineer specializing in the semantic infrastructure that makes AI systems reliable. My work sits at the intersection of data architecture, applied AI, and organizational change:

• Infrastructure & Ontology. I transform raw data into AI-First foundations—audit-ready, silo-free architectures where every financial and operational decision draws from a single source of truth. Recent work includes designing the enterprise semantic stack for Farmland LP, the largest US fund manager focused on organic and regenerative farmland, where a formal OWL ontology and knowledge graph unify accounting, GIS, and field operations into one machine-readable layer. I’ve also built an open OWL ontology that translates thirty years of conservation frameworks into queryable knowledge graphs for portfolio-wide reasoning.
• AI Innovation & Prototyping. I deliver high-value AI capabilities that dramatically reduce the latency between inquiry and action. This includes Retrieval-Augmented Generation (RAG) pipelines for natural-language querying of unstructured data, agentic workflows where autonomous AI agents reason across the ontology to answer complex “what-if” scenarios, and advanced visualization that integrates geospatial and financial data into a single pane of glass. For the Walton Family Foundation, I built an LLM-powered extraction pipeline that synthesized thousands of narrative reports into a dynamic, portfolio-wide impact map. At USAID Guatemala, I designed the data architecture that consolidated 60+ disjointed trackers into a centralized, geospatial data ecosystem.
• Adoption & Value Realization. Technology only creates value when people adopt it. I practice what I call Adoption Engineering—stakeholder shadowing, internal champion development, and workflow migration strategies that ensure new systems translate directly into measurable operational efficiency. This includes establishing ROI frameworks, creating technical documentation and training materials, and building the organizational muscle for long-term self-sufficiency.

Tuck Labs

I founded Tuck Labs, LLC to help small and mid-size businesses establish AI-First data foundations—the semantic infrastructure most organizations skip on the way to deploying AI. Tuck Labs delivers three pillars of service: Foundation (structuring institutional data and knowledge into connected, audit-ready knowledge graphs), Capabilities (deploying RAG pipelines, agentic workflows, and decision-support tools that turn information into instant strategic insight), and Value (the adoption engineering, change management, and organizational L&D required to make it all stick). The thesis is simple: the right order is Data → Semantics → Ontology → Agents—and skipping the middle steps is why most AI initiatives underdeliver.

Background

I studied environmental science with a focus on economics at Colorado State University, where I was a fellow with the Center for Collaborative Conservation and helped develop work that eventually launched as the Peaks to People Water Fund. I returned to school in 2024 to earn a Master’s in Data Science from the University of Colorado, Boulder, and hold the Earth Lab’s Earth Data Analytics Professional Certificate.

My career began on the ground—protecting and restoring natural areas in Colorado and working directly in conservation and mitigation banking. At the Colorado State Land Board, I helped monetize ecosystem services, leading to the first conservation bank on state trust lands. That work led me to Environmental Incentives, where I found my niche leading interdisciplinary teams of scientists, academics, and practitioners to develop science-based methods for measuring conservation outcomes at scale.

I developed the crediting protocols for the Nevada Conservation Credit System and adapted them for programs across five western states for the greater sage-grouse. I went on to develop similar approaches for the monarch butterfly and other pollinators, working with collaborators from Mexico to Canada. For this work, our consortium was awarded the Natural Resource Conservation Achievement Award from the U.S. Geological Survey.

That chapter taught me how to build simple, scalable measurement systems—and the data infrastructure to support them. As a consultant to the U.S. Agency for International Development (USAID), I brought those skills to teams around the world and discovered that knowledge management, not just data management, was the limiting factor for program efficacy. I built data hubs like the Guatemala Data Hub¹ and began using knowledge graphs and large language models to unlock scientific and institutional knowledge across large organizations—work that set the trajectory for everything I do today.

Clients & Partners

Past and current clients and partners include Farmland LP, the Environmental Defense Fund, Walton Family Foundation, State of Colorado, Nevada Department of Conservation, Idaho Fish and Game, The Nature Conservancy, U.S. Agency for International Development, University of Minnesota, and many others.