DATA, AI & TECHNICAL CONSULTING
I help businesses turn scattered information into useful decisions, build practical AI tools, and develop ideas into products and services. We start with a clear problem and a result you can inspect.
For small and medium businesses, engineering firms and science teams. The work might involve predictive modeling, a better website or business workflow, or a scientific question that needs careful analysis.
Currently booking engagements for fall 2026.
A starting point for your business
A small project can stand on its own. We'll agree on what you need, what you'll receive, and how we'll check it before work starts.
Small and medium businesses
Customer inquiries, quoting, reporting and handoffs can consume the day. Bring the problem and the tools you already use. We can scope a website, a focused business tool, or help with one recurring task.
Discuss a small-business project →Engineering and science teams
When the output informs an engineering or scientific decision, the evidence matters. I help with source-grounded analysis, technical workflows, R&D decisions and AI evaluation, with expert review built into the work.
Explore technical services →Four steps, each its own engagement. One ends in working code. The other three end in a written record you keep.
A half day on one workflow with the people who run it, then a short readout: where the friction is, and whether the Sprint is the right next step.
Teardown details →Three calendar weeks on one workflow. You leave with a pilot specification and a build, narrow, defer, or stop decision.
Sprint details →If the decision is build, the pilot runs in your environment on representative inputs, with agreed acceptance criteria and run records you can inspect.
Pilot details →After the pilot proves out, or in place of one, advisory continues as a monthly retainer: a standing review cadence, a named response window, and a written advisory record. You opt in, and you can end it in any month.
Advisory details →For workflows that need deeper assessment · AI Workflow Diligence Sprint
Three calendar weeks after kickoff and receipt of the agreed source material
Models that inform decisions, AI that works with your information, and tools built around a real business need. These examples show how I combine analytical work, software and scientific judgment. Each case names its original context and development stage.
Flagship case study · Commercialized product
I brought scientific modeling, product development and customer economics together to turn a research program into a commercial decision tool at Cargill.
The original problem was poultry nutrition. The broader capability is turning complicated data into useful recommendations, making the service affordable to deliver and giving customers a reason to adopt it.
$180 → $25per-sample analysis cost
Read the flagship case study →Cargill Animal Nutrition · 2015–2018 · Historical employment work
I built tools for reusing prior work, assembling proposal drafts and producing supporting documents. The wider opportunity is recurring business writing that starts with information your team already has.
Status Team use reported; business-impact metrics not established
Read the walkthrough →
I built a document-retrieval system that connects answers to supporting passages. It demonstrates how AI can help people work with a body of information while keeping the evidence available for review.
Status Built and tested on a small, controlled document corpus
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I designed engineering prototypes to assemble information, extract requirements and flag discrepancies. The capability is turning fragmented files and repetitive checks into a tool a specialist can review.
Status Prototype design; no real-project results claimed
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A synthetic-data feed-formulation example connects cost, requirements and input quality. It shows how a decision model can make tradeoffs visible and help a user trace the assumptions behind a recommendation.
Status Illustrative data; no client results or completed implementation claimed
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I developed organism strategy, a conceptual bioprocess and technical-economic analysis for a space-biomanufacturing study. The practical skill is comparing technical options against the resource that actually limits the project.
Status Conceptual design and analysis; not deployed hardware
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I built a biological reference catalog that connects findings to their sources and grades their supporting evidence. It demonstrates research synthesis and a disciplined way to distinguish strong support from uncertainty.
Status Evidence catalog; grades support expert review
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I built an analytical evidence system that updates competing explanations as new information arrives. It makes uncertainty visible and identifies when the available evidence is insufficient for a conclusion.
Status Evidence-assessment software; conclusions require qualified review
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I built a scientific knowledge-graph proof of concept that connects records from different sources and preserves their provenance. It shows how linked information can remain inspectable as it moves through an analytical workflow.
Status Research proof of concept on a bounded dataset
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An illustrative proposal review connects a technical concept to funding criteria, evidence gaps and a revision plan. It shows how I structure a difficult technical decision before more writing or development begins.
Status Illustrative service walkthrough; not a client result
Read the walkthrough →These are career precedents, not consulting-engagement results. They show the same discipline the Sprint applies: process design and technical systems that had to hold up at commercial scale.
I led the development and commercialization of Galleon™ Broiler Microbiome Intelligence. Per-sample analysis cost fell from $180 to $25, making routine customer testing economically practical.
Galleon™ Broiler Microbiome Intelligence (Cargill) · 2023 Gold Edison Award winner
At Elanco, I owned HTSi strategy, vision, roadmap and analytics direction, coordinating R&D, marketing and sales. A 2020 study reported adoption of HTSi and its intestinal-integrity index by customers in over 62 countries during my tenure.
Elanco · HTSi product ownership · 2020 platform adoption study
Read the 2020 adoption study →At Land O'Lakes, I monitored the PMI portfolio against business goals, built dashboards and led go/no-go decisions. I also led customer relationships and intellectual-property strategy for the portfolio.
Land O'Lakes · PMI Business Portfolio
AI is very good at doing the wrong thing correctly. The discipline below is how I catch the confident wrong answer before it reaches your workflow.
Read the full method →The agent works in a contained workstation with the tools it needs and nothing else, walled off from your network and operations.
AI-built work routinely passes its own tests and still does nothing in the real flow of the job. I check the work in that flow, on the inputs and handoffs the job actually has, before it counts as done.
Where a value has to be right, it comes from the source document, the published table, or a federal data feed, with a citation. Never from the model's guess.
I am not a domain expert in everything I touch. Your domain experts review the output before it ships. My job is the workflow map and the build path, not overriding your judgment.
These are the capabilities that feed a Sprint or follow from it. They are the same method applied to the decisions around automation, not a separate line of business.
Building and hardening the automation itself, once the Sprint has scoped it.
Deciding what is worth building, and proving the case before capital is committed.
Getting technical work funded and understood by reviewers, boards, and the public.
Founder & Principal Consultant
I help business owners and technical teams turn a problem into a scoped project, a working tool or a decision they can act on. My consulting work includes workflow design, applied AI and technical advisory.
My background includes product commercialization at Cargill, product ownership at Elanco, R&D portfolio governance at Land O'Lakes and scientific evaluation at Signature Science. I hold a PhD in Microbiology from the University of Tennessee, Knoxville, and am a named inventor on two granted US patents.
Hiring for your team? View my employment portfolio →
Named inventor on granted US patents in metabolic engineering and yeast biosystems, and co-inventor on a published microbiome-analytics patent application. Doctoral research on the transcriptional response of microbial systems to chemical stressors. Everything below is on file and verifiable.
Patents & Applications
Research & Recognition
Bring one workflow that is slow, manual, or too fragile to automate blindly. In 30 minutes we decide whether it is a fit for the Sprint, needs a narrower first step, or is better left alone.
