AI strategy & advisory.
Before writing any code, we map your data assets, systems, regulatory constraints and internal skills. The deliverable: a costed, sequenced roadmap with the use cases worth launching, and the ones to rule out.
What the engagement covers.
- 01
Full diagnostic
Audit of data assets, existing architecture, governance, internal skills, regulatory and security constraints. We look at everything, no marketing filter.
- 02
Use-case landscape
Wide identification of AI opportunities across your operations, ranked by business impact, complexity, risk and technical feasibility.
- 03
Costed prioritisation
For each retained use case: estimated ROI, build cost, lead time, dependencies, success metrics. Numbers replace opinions.
- 04
Executable roadmap
6 to 12 months execution plan, sequenced into quick wins and deeper bets. Documents ready for the boardroom, not another PDF.
Three to six weeks, from diagnostic to roadmap.
Framing
Kickoff workshop with founders, COO and ops leads. Alignment on business goals, constraints and success criteria. Output: validated scope, calendar, stakeholders.
Field diagnostic
3 to 5 deep workshops: data, systems, teams, processes. Interviews with target users. We chase the truth in actual workflows, not in decks.
Mapping & prioritisation
8 to 12 candidate use cases scored on ROI, complexity, risk. Iterate with your team to validate business hypotheses before locking the roadmap.
Executable handover
Costed roadmap, sequenced execution plan, build/buy/team recommendations. Boardroom presentation if needed, artefact transfer to your team.