More AI ≠ Good AI.
Build Good AI that earns its place.
We help leadership teams decide what to pursue, what it will take, and whether the work deserves further investment.
Independent strategy, adoption, and project oversight grounded in real work and measurable outcomes.
We care about solving the problem,
not selling the most complicated version of it.
Where AI already helps, and where it doesn't.
What the work has to change to be worth it.
Getting people to use it, and use it well.
Measured outcomes, reviewed before the next spend.
From opportunity to lasting change
BGAI helps organizations identify where change is worth pursuing, design a practical path forward, test promising solutions, and build the conditions for adoption.
Ideas ≠ decisions.
Discovery & Opportunity Sprints
Find and prioritize the problems worth solving.
Typical engagement: 2–4 weeks
A vision ≠ a plan.
Product & Transformation Strategy
Turn priority problems into an actionable strategy and roadmap.
Typical engagement: 4–8 weeks
Access ≠ adoption.
Adoption & Enablement Workshops
A 1–2 day workshop to start adoption in real work.
Typical engagement: 1–2 days
A roadmap ≠ results.
AI Transformation Studio
Move selected opportunities from concept to validated practice.
Typical engagement: Defined build cycles or embedded partnership
Selected organizations where our founders led this kind of work.
Real work. Measurable results.
Build Good AI is new. The work behind it is not.
We know how to pull complicated, disconnected pieces together and turn them into something that works.
| Result | What changed | Context |
|---|---|---|
| 23 → 4 | Experiments narrowed to four funded pilots with owners, measures, and cost ceilings. | AI opportunity decisions · Developer tools |
| 89% automated | Contract reconciliation automated end to end, with exceptions intentionally retained for people. | Finance operations · Developer tools |
| 700K decisions/day | Production AI operated with documented accuracy and precision. | Trust and safety · Music platform |
These outcomes reflect our founders’ AI work before Build Good AI.
Different backgrounds. A lot of the same lessons.
Meet the people behind Build Good AI.
CEO
Marla Johnson
Entrepreneurship · Growth · Commercialization · Capability building
Marla knows how to turn an opportunity into a business.
COO
Brad Wood
Operations · Healthcare staffing · Retail · E-commerce
Brad knows what it takes to keep a business running.
CAIO
Katy Simmons
AI transformation · Product · Operating systems
Katy redesigns how organizations work with AI
Why Build Good AI?
There is a large gap between what AI can do in a demonstration and what an organization can use reliably on a Tuesday afternoon.
Build Good AI works in that gap: between an opportunity and a sound investment decision, between a product vision and the organization required to deliver it, between access to AI and the ability to use it well, and between project activity and evidence that the work should continue.
AI can make information more accessible, reveal useful patterns, reduce repetitive work, and make some problems approachable that once required more time, money, or specialized expertise. That potential is worth pursuing.
But someone still has to decide what matters, what should be built, which decisions belong to people, what evidence is good enough, and whether the next phase has earned its investment.
We think those decisions deserve at least as much attention as the technology.
That is what we mean by Build Good AI.
More AI ≠ Good AI
Bring us the messy version.
The workaround everyone hates. The AI tool nobody uses. The project update that never proves anything. The idea that might be valuable, if you could determine what it would take.