Ready for AI, but not sure where to start?
That's the right time to talk. I help small to mid-market companies and individuals take the first real step with AI — finding where it genuinely fits your business, then building something that works. Not someday. This quarter.
Where AI adoption takes flight.
The work
How the work unfolds
Each stage stands on its own. Most companies start with the Assessment and decide from there.
- STAGE 01
First Light
AI Readiness Assessment — where AI helps, and where it won't.
2–3 weeks
- STAGE 02
Take Flight
Adoption Roadmap — sequence, owners, budget, and the first pilot defined.
3–4 weeks
- STAGE 03
Fly On
Pilot Implementation — into production, without breaking things.
6–12 weeks
- STAGE 04
Never Broken
Optimization & team enablement.
Engagements
Three ways to work together
These aren't rigid packages — most projects blend all three, tailored to fit your budget and your timeline. Every engagement is scoped in plain language before anything is signed.
Fixed scope
A defined outcome, timeline, and price agreed up front. Assessments and roadmaps run this way — you know exactly what you're getting and what it costs before we begin.
Time & materials
For work that needs room to move — pilots, integrations, and builds where the path sharpens as we go. Billed as we work, transparent, and easy to pause.
Consultation
A standing line to someone who's done this before. Questions answered, vendors evaluated, decisions pressure-tested — judgment on tap, without a project attached.
Selected work
Things I've built with others
A few of the systems I've helped teams ship. Details shared in conversation — some work stays confidential.
Custom proposal generator
Every proposal was assembled by hand — scope, pricing, boilerplate — eating senior hours on every deal. Built a generator that drafts complete, priced proposals from deal parameters, so the team starts from a near-final draft instead of a blank page.
Biotechnology · Commercial operations
Automated revenue forecasting
Forecasts lived in spreadsheets that were stale the day they shipped. An automated pipeline now assembles bookings and revenue projections continuously — a quarterly scramble became a standing view of the business.
Finance · Planning and analytics
Lean operations toolkit
Small operations don't have a bench of analysts. Agentic org charts and budget management tools now carry the coordination and tracking a back office would — so a lean team runs like a bigger one.
Small operations · Business management
About
A practice of one, on purpose.
Twenty years in biotechnology — from the manufacturing floor, through project management, to leading commercial operations. Along the way I built the systems the business actually ran on: proposal generation, pricing models, revenue forecasting, planning and analytics. When AI got good enough to do real work, I rebuilt them with it — and watched hours come back every week.
What started at work followed me home: a travel planner, a fantasy football portal, grading automation for teacher friends. When colleagues saw what these tools could do, interest turned into engagements, and the engagements became this practice.
Every engagement starts with the same question: what are the five biggest time sucks of your week? Then we build from there — your expertise in your business, my experience putting these tools to work in the real world. When you hire the practice, you get me: one practitioner, a few clients at a time, small by design.
The approach
You don't have to figure this out alone. The first step is an assessment, not a sales pitch.
The tools are good enough now — that was the hard part, and it's solved. What's left is the judgment: which problems AI actually fits, what your business needs in place first, and how to start small enough to succeed. That's what I bring — without the enterprise price tag or a firm that ships slide decks instead of software.
Contact
Begin the conversation.
A 20-minute call to see whether there's a fit. If there isn't, I'll tell you.
Prefer email?
