Best for
- Leadership teams pressured to "do AI" without a clear plan
- Companies with multiple half-built AI experiments and no integration story
- Boards or investors asking for a credible AI thesis
What you get
- Written roadmap: 6–12 prioritized AI initiatives with rough cost and ROI
- Honest assessment of what to deprecate, pause, or kill
- Build vs. buy guidance per initiative — model, infra, and vendor recommendations
- A sequencing plan so each initiative compounds the next (data, evals, agents)
- Two presentation sessions: one with leadership, one with engineering
- A 1-page board-ready summary
How it runs
- Days 1–2Stakeholder interviews + audit of existing AI work and data.
- Days 3–5Opportunity surface: brainstormed list scored on cost/value/risk.
- Days 6–8Drafted roadmap + build/buy guidance. Internal review with you.
- Days 9–10Final document, leadership presentation, engineering walkthrough.
Not included
We are honest about scope so engagements stay sharp. These items live elsewhere or are deliberately out of scope for this engagement type.
- Implementation work (move to a Sprint when you are ready to build)
- Vendor procurement or contract negotiation
- Ongoing strategic advisory (move to Embedded)
Common questions
Can you also build the things you recommend?
Yes. Most strategy engagements turn into a sequence of two-week Sprints. There is no obligation — many clients use the roadmap with their internal team or another vendor.
How is this different from a typical consultancy strategy deck?
Three ways: (1) it is written, not slides — your team can actually execute from it, (2) it includes honest stop/kill calls, not just additive ideas, (3) every recommendation has a build path with realistic cost and timeline.
Do we need to share confidential data?
Only as much as you want. We can work entirely from interviews and public information, or sign an NDA and dig into your stack and metrics. Both produce useful roadmaps — the latter is sharper.
Other engagements
Ready when you are