Resources · Self-assessment
9 questions, 5 dimensions, an honest score. No hype.
We score data, process, team, tooling, and risk. Honest > optimistic.
01 · Data foundation
Where does the data your team operates on live?
02 · Data foundation
How clean and labeled is your historical data?
03 · Process clarity
Are your top 3 workflows documented?
04 · Process clarity
Can you identify 1–2 manual tasks taking >10h/week each?
05 · Team & ownership
Is anyone on the team comfortable with prompts and AI tools?
06 · Team & ownership
Who would own a new AI workflow once it ships?
07 · Tooling baseline
Do you already use SaaS with APIs (CRM, accounting, comms)?
08 · Risk & budget
What's your tolerance for an AI mistake in this workflow?
09 · Risk & budget
Do you have a budget for an AI pilot in the next 90 days?
Awaiting answers
Answer the 9 questions to see your score.
We score 5 dimensions: (1) data foundation — is the data centralized and clean enough to feed a model; (2) process clarity — are the workflows documented; (3) team and ownership — does someone own AI in production; (4) tooling baseline — modern SaaS with APIs; (5) risk and budget — tolerance for mistakes and pilot budget.
Most failed SMB AI projects fail at the data step. If the model can't reliably read your data, prompt engineering on top doesn't save it. Centralized + labeled data is the prerequisite, not the optimization.
That's the common SMB pattern. The recommendation is still 'pilot on a low-risk internal workflow' — but the focus is on owner assignment and AI literacy training before scaling.
No. The math runs in your browser. We only know your aggregate score if you book a call and tell us — we use that to skip ground we'd otherwise have to cover in the diagnostic.
