VERIFIED WORKFLOW ENGINEERING

Build AI workflows your team can trust.

I map the process, separate deterministic work from model-assisted work, and scope one pilot with traceable outputs, human review, and a clear stop condition.

For science and engineering teams already using AI tools but still doing the real workflow by hand.

See if the Sprint fits See a worked example →
Science & engineering teams Client-owned implementation Every critical output traced or flagged
Workflow pipeline diagram: raw inputs through clean, model, and a go/no-go decision gate to a named deliverable.
Every engagement ends in a named deliverable and a clear stop condition, not a capability deck.

The first engagement

Start with one workflow, one decision, and one pilot scope.

From $12,000 · Three calendar weeks after kickoff and receipt of the agreed source material

Bring one technical workflow that is slow, manual, or too fragile to automate blindly. I map how the work happens now, find the parts worth testing, and give you a pilot scope you can choose to build or reject.

You bring

  • Access to the people who run and own the workflow
  • Representative inputs and outputs from the workflow
  • Existing SOPs, process notes, or examples of how the work is done
  • Known security, regulatory, quality, or IP constraints
  • A decision-maker who can evaluate the proposed pilot

You leave with

  • A current-state workflow map
  • A time and cost baseline where the available evidence supports one
  • A record of the handoffs, review points, and failure consequences
  • A breakdown of deterministic, model-assisted, and human-judgment steps
  • A risk-and-value ranking of the possible automation points
  • One bounded pilot specification with inputs, outputs, acceptance criteria, and stop conditions
  • An implementation estimate for that pilot
  • A build, narrow, defer, or stop decision memo
See if the Sprint fitsRead the full offer details →
Worked examples

Three domains, one way of working.

Each one shows the same method on a different problem: map the workflow, automate the parts that are safe to automate, and keep a domain expert on the rest. The domain changes. The method holds.

Drainage-area summary tool output.
Prototype
Workflow mapping: civil engineering Prototype build note

Drainage studies lose too many hours to data assembly.

Three prototype tools I designed in response to friction I observed in conversation with civil and water-resources engineers: drainage-area summaries, ordinance-criteria extraction, and Civil 3D vs SewerGEMS plan QA. Advisory only, every value cited or flagged for review.

Status Prototype design, not a delivered engagement

Read the walkthrough →
Abstract gap-map analysis: a ruled proposal overlaid with an analytical grid marking points of reviewer risk.
Illustrative engagement
Workflow mapping: federal proposals How I would architect

How to review a stalled SBIR draft against the criteria that decide it.

An illustrative walkthrough of a criterion-linked review: solicitation map, prioritized gaps, technical-thesis pass, revision roadmap, and submission decision memo.

Example deliverable set Solicitation-specific review map · prioritized gaps · revision and decision plan

Read the walkthrough →
Abstract orbital bioprocess: a small bioreactor over a planetary horizon, joined by a sealed closed-loop flow.
Published/conceptual work
Workflow mapping: biotech R&D Conceptual TEA

Most techno-economic analyses minimize dollars. This one minimized mass.

A conceptual TEA of fermentation aboard a space mission, under DARPA BSURE. When the scarce resource is launch mass rather than dollars, the cost of every input is repriced. The transferable part is choosing the right objective function before building the model.

Outcome 258 kg/yr lactic acid from a 10 L orbital bioreactor · yeast platform 37% lower system mass · conceptual TEA, FOCAPD 2024

Read the walkthrough →
All case studies →
Method

Reliability is the product.

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 →

  • Sealed workshop, not loose in your systems.

    The agent works in a contained workstation with the tools it needs and nothing else, walled off from your network and operations.

  • Real-workflow checks, not just passing tests.

    AI-built work routinely passes its own tests and still does nothing in the real flow. I check it against the actual persistence and command paths before it counts as done.

  • Every number cited to a source.

    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.

  • Domain-expert review, every time.

    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.

Track record

A track record of technical systems that had to work in the real world.

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. The current AI workflow-engineering examples are prototypes and conceptual work, and stay labeled that way until the first paid engagement is cleared for publication.

≈ 86% per-sample cost · production scale

A microbiome analytics platform commercialized as Galleon™ Broiler Microbiome Intelligence reduced per-sample analysis cost by approximately 86% at full production scale. The 2023 Gold Edison Award recognized the platform that resulted.

Galleon™ Broiler Microbiome Intelligence (major animal-nutrition company) · 2023 Gold Edison Award winner

> 80% of the global poultry market reached

An animal-health diagnostics platform I led the technical build of now reaches more than eighty percent of the global poultry market. The same discipline drives every Lab-to-Plant Process Plan engagement: process design that survives the jump from lab to plant.

Animal-health diagnostics platform · commercial deployment

Multiple technologies advanced to proof-of-concept

Multiple technologies moved from concept to validated proof-of-concept under a single coherent IP strategy for a major animal-nutrition business. Three related filings are named-inventor US patents on record.

IP strategy engagement · animal-nutrition R&D portfolio

Anonymized third-party engagement quotes are added as engagements ship and clients clear them for citation.

Supporting capabilities

The same method, applied across the work around the Sprint.

These are the capabilities that feed a Sprint or follow from it. Each is a place the method has already shipped, not a separate buyer lane.

Workflow Engineering

Building and hardening the automation itself, once the Sprint has scoped it.

Scientific & R&D Decision Support

Deciding what is worth building, and proving the case before capital is committed.

Federal & Technical Communication

Getting technical work funded and understood by reviewers, boards, and the public.

See all capabilities in detail → Download capability statement →
Dr. Vernon McIntosh, AI/ML workflow engineer and consultant
About

Dr. Vernon McIntosh

Founder & Principal Consultant

I am an AI/ML workflow engineer and consultant. My core is composing your current process into an automation pipeline your team trusts, with fidelity, reliability, and security designed in. The cross-domain range is proof the method transfers across fields: a microbiome analytics platform that reduced per-sample cost by approximately 86% and won the 2023 Gold Edison Award, a diagnostics platform reaching more than 80% of the global poultry market, multiple technologies moved to proof-of-concept under one IP strategy, and named-inventor US patents in metabolic engineering and yeast biosystems. PhD in Microbiology from the University of Tennessee, Knoxville.

McIntosh Consulting is an independent advisory practice. I hold an outside-employment authorization from my primary employer; all McIntosh Consulting engagements are contracted directly with this practice. Standard vendor-onboarding artifacts (W-9, certificate of insurance) are available on request.

AI/ML Workflow EngineeringAutomation & Data ScienceMetabolic EngineeringFederal Proposal SystemsCivil Engineering Tooling
Patents & Publications

The record, on file.

Named inventor on granted US patents in metabolic engineering and yeast biosystems. Doctoral research on the transcriptional response of microbial systems to chemical stressors. Everything below is on file and verifiable.

Patents & Applications

Research & Recognition

  • PhD Dissertation An Analysis of Global Gene Expression Resulting from Exposure to Energetic Materials University of Tennessee, Knoxville · 2010
  • Recognition Galleon™ Broiler Microbiome Intelligence: 2023 Gold Edison Award Major animal-nutrition company · Edison Awards · 2023
Insights

Practical notes for teams moving AI into real work.

Perspectives on AI systems, R&D, and engineering workflows.

AI Engineering

You Bought the AI Licenses. Here's Why Your Team Still Uses It Like a Chatbot.

Copilot, ChatGPT Enterprise, and Claude seats got approved months ago. Most of your team still opens a chat window, pastes something in, and copies the answer back out by hand.

 Data Science

From Spreadsheet to Workbench: Automating the Data Assembly Around Your Modeling Software

HydroCAD, SewerGEMS, and Civil 3D are not the bottleneck. The hours your engineers lose reformatting spreadsheets before the model even opens are.

 Data Science

Every Number Cited or Flagged: Building AI Workflows an Engineer Can Audit

AI output stalls at interesting and never reaches shippable for one reason: you can't trace the numbers. Here's what a provenance-clean workflow looks like, and why it's the difference between a demo and a deliverable.
All insights →
Get started

Bring one workflow.

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.

See if the Sprint fits Email directly →