Analyze processes, data sources and systems: access, data quality, interfaces and technical limits
AI feasibility check. Clarity before investment.
I examine your processes, data and systems and specify the strongest use case. The result: go, no-go or not-yet — with an implementation specification, prerequisites and effort range.
- Duration
- 1–2 weeks
- Pricing model
- Fixed price · on request
What I assess — and what you can decide next
Assess use cases from both an engineering and commercial perspective: value, feasibility and effort
Plan the strongest case: scope, acceptance criteria, prerequisites and implementation frame
When WDC fits. What you leave with.
When this service fits
- AI is on the agenda. Data readiness, feasibility and integration effort are still unclear.
- Several ideas compete for budget. A technically sound assessment is missing.
- An early prototype failed or stalled. The cause is unclear.
What you have after the project
- Go, no-go or not-yet — justified from both an engineering and commercial perspective
- An implementation specification with scope, acceptance criteria, prerequisites and effort range
- A shared basis for decision across management, IT and operations
What a project looks like in practice
Twelve ideas. One viable case.
A mid-sized company has twelve AI ideas. Which one is technically viable and commercially sound is still an open question.
Departments assess value, data readiness and effort differently. Budget is available. A sound technical basis for the decision is missing.
I analyze processes, data sources and systems, assess every idea for value, feasibility and effort, and specify the strongest case.
One case receives a clear go and an implementation specification. Two receive a not-yet decision. Unsuitable ideas end with a justified no-go.
Verify first or build now?
Describe your case and I'll tell you whether to verify first, build now or deliberately not invest.