We help small teams
build and innovate
with AI.
Fractional Chief AI Officer for mid-market teams. We help you find the AI projects that are actually worth doing, build the first real version, and walk away from the ones that won’t pay off. One senior person on the work — not a pod of juniors.
- 6-month engagements
- $5–15k/mo
- In production at CPG, B2B, Health Tech
- Cost of a CAIO
- $400k → ~$10k/mo
- Engagement
- 6 mo
- Initiative portfolio
- 3 / 7
Full-time vs. fractional
Then quarterly
Bets per quarter
The 30-second version:
- What it is
- 0→1 AI Partner (operating as a fractional CAIO)
- Who it's for
- Small teams taking on big AI initiatives
- Pricing
- $5k–$15k/mo — fixed retainer or capped days
- Engagement
- ~6 months, then quarterly
What this actually looks like.
A full-time CAIO: $400k + equity + 12 months to hire.
Strategy
- 01
We sit in on the big AI decisions.
In the room when the call gets made — not reading about it in a report a month later.
- 02
We say no to the projects that won’t pay off.
Most don’t survive an honest look at the numbers, and it’s far cheaper to find that out now than at the end of the year.
- 03
We keep your list of AI bets in order.
Three to seven at a time, each one weighed on effort, risk, and what it does for the bottom line.
- 04
We write the briefs your team builds from.
A clear picture of what “done” looks like — and what we’re deliberately leaving alone this quarter.
- 05
We read the vendor contracts before you sign.
Especially the ones a salesperson swears are “just a pilot.”
Build
- 06
We build, when building is the right call.
Make a first version, get it working in front of real people, and hand it over to your team.
Three things. One person.
Most people in this market sit in one circle. A few sit in two. Almost nobody sits in all three.
The rare overlap — strategist, builder, end-user obsessive — in one person.
What your senior team’s week looks like on AI.
This is the second way we work. The company retainer is about the business as a whole; this one is about the people running it — how your CEO, COO, and CFO actually use AI in their own week.
- 01
We get your leaders set up with AI that works for them.
We start everyone on Claude — it’s the most accurate on real business work, writes in the most natural executive voice, and is the easiest to defend on data security.
- 02
Nothing important slips through the cracks.
Your meeting notes and Slack threads get pulled together automatically, so the action items and who owns them land in front of you on a regular schedule.
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★ Most requested
03
A chief of staff for every leader.
Each person gets their own private AI setup — loaded with their context and their routine tasks, and tuned to the way they actually make decisions.
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★ Most requested
04
Board-ready decks without the back-and-forth.
We load your brand’s look and voice into the tools, so a CEO can turn out a polished one-pager or board deck without sending it back to marketing three times.
- 05
A clear read on where AI helps — and where it shouldn’t.
We map out each leader’s responsibilities and sort them into three buckets: where AI can do the work, where it can assist, and where it should stay out of the way.
- 06
Help hiring people who already think this way.
We’ll show you what to listen for in a thirty-minute interview. It’s not a job title — it’s a way of working.
It’s a different shape from the company retainer: usually a focused stretch of six to ten weeks that ends with your senior team running comfortably on their own. Book a call →
Mid-market AI, right now.
- Your board wants an AI strategy.
- Your inbox has forty vendors offering one.
- Three of your VPs have already bought something on a company card.
A company your size gets maybe two or three real shots at this a year. Betting on the wrong ones costs you far more than doing nothing would.
Someone senior has to make the calls. That’s what we do.
Three problems, recently solved.
- CPG № 004.1
Hundreds of customer messages a week, handled without hiring a support team.
An assistant that answers customer emails and phone calls, backed by the rules and hand-off logic that make it feel like a real teammate.
Direct-to-consumer · In production Read CloseThe problem. Top Cup’s direct-to-customer sales took off, and customer messages went from a trickle to hundreds a week — order updates, sizing questions, custom requests, returns. Hiring a support team to keep up would have eaten most of the profit the new sales channel had just created.
What we did. We built Luna, an assistant that answers customer emails and phone calls. The assistant itself is almost the easy part now; the real work was everything underneath it — the policies, the tricky edge cases, knowing when to hand a conversation off to a person, and learning from each one — so that Luna feels like a helpful teammate instead of a frustrating bot. Top Cup grew the new channel without growing its payroll.
- B2B № 004.2
More sales from the same size sales team.
Instead of hiring more salespeople, we gave the ones they had better information: which customers are about to leave, who to call, and when.
Sales intelligence · Engagement Read CloseThe problem. A mid-market company that sells supplies to other businesses wanted to grow. The usual answer — hire more salespeople, at roughly $120k each once you count everything — was slow and expensive, and the reps they already had were spending their time on the wrong accounts.
What we did. Rather than add headcount, we gave the existing team a much clearer picture of their customers. The system spots accounts that are about to drift away before a rep would notice, reminds them to reach out as a customer comes due for a reorder, and points them toward the right new prospects at the moment those prospects are actually ready to buy — not a quarter too late. The team didn’t get bigger; it got a far better map of where to spend its time.
- Health Tech № 004.3
From a year to build and test an idea, down to two weeks.
Two AI systems working side by side — one to find which version of the business actually made money, the other to quickly build working versions to put in front of real customers — so the team could stop guessing.
Venture-backed · Engagement Read CloseThe problem. A venture-backed health tech company had spent a year on a product that wasn’t catching on. Before they wrote any more of it, they needed to know which version of the business actually worked — different prices, different types of customer, different ways of delivering the service.
What we did. We set up two AI systems to work side by side. The first ran the numbers on every combination of price, cost, sales channel, and customer type, and ranked them by which ones actually made money. The second quickly turned the most promising of those into real, working versions the team could put in front of actual customers. What used to take a year to build and test now took two weeks — so instead of arguing over which version of the company to build, they could simply try it and find out.
Aaron.
Two decades as the person a CEO calls when a new initiative needs to get off the ground. Most of that was pre-AI — ops, product, go-to-market. The tools changed. The job didn’t.
Now the work is helping small teams figure out which AI bets are worth making, then building the first version of the one that is.
- 01Strategist
- 02Builder
- 03End-user obsessive
Stealthy Good is based in Boone, NC, and takes a small number of retainers at a time.
Notes on AI, mid-market, and the vendor-industrial complex.
Published occasionally. Written for operators, not marketers.
- 10 min
Mythos just moved the goalposts on software security.
What to do if you’re not a Fortune 500 bank — and why specialized software vendors are the ones most exposed.
- 9 min
AI at work isn’t a technology problem.
Why most rollouts are stalling — and the three things mid-market leaders should actually be focused on.
- 7 min
Most of this won’t work.
On the discipline of killing AI initiatives before they eat your quarter.
Questions you were going to ask on the call anyway.
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What does this cost?
$5–15k/mo, fixed or capped-days. Numbers on the intro call, not a “contact sales” maze.
Two shapes. Pick the one that fits how you work:
Fixed-fee retainer. One number per month. I figure out how to add the most value against the priorities we set together. Best when the work is fluid and you trust me to run at it.
Capped-days retainer. 3 to 6 days a month, your pick. Best when your finance team wants a line they can audit, or when your scope is well-defined.
Both $5k–$15k/mo depending on scope. Both renewable quarterly after the first six months. Full pricing on the intro call — no “Contact sales for pricing” nonsense, you’ll hear a number within the first 20 minutes.
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How long does an engagement last?
Six months, then renewed by the quarter. Most useful work happens in months 2–5.
Typical retainer is six months, renewed by the quarter after that. Most useful work happens in months 2–5. We’ll tell you when to stop; that’s part of the job.
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What’s out of scope?
No full-time placement, no 200-person programs, no crypto.
A few specific things we don’t do:
- Full-time executive placement
- 200-person implementation programs
- Computer-vision consulting for autonomous vehicles
- Crypto
- Chatbots whose only job is to be a chatbot
If the work doesn’t change a number on your P&L within a year, we’re probably the wrong firm.
If you got this far, you probably already know whether we’d be useful.
Thirty minutes, no slides, no discovery-call theatre. Bring the problem you’re actually stuck on. We’ll tell you if we can help, and if we can’t, who might.