Service · Wolff Applied AI
From a prioritised use case to a secured go/no-go decision — before budget flows into the build.
The bridge between strategy and implementation: within 2–3 weeks we scope your prioritised use case in detail, check data situation and feasibility, and sketch a solution and architecture option (make/buy, RAG vs. API vs. fine-tuning, M365 integration). We assess the economic viability with traceable ranges. You receive a well-founded go/no-go recommendation together with an implementation roadmap and a risk classification.
The bottleneck rarely lies in the idea but in the transition from pilot to production: according to S&P Global (2025), 42% of companies abandon the majority of their AI initiatives before productive deployment. The most common stumbling blocks before the build are unclear data availability and quality (~43%) as well as technical immaturity (~43%) — both can be checked in advance instead of being discovered during the project. A build project, once started, quickly ties up five- to six-figure budgets; an upstream feasibility and economic viability check reduces the risk of costly misinvestments. Many organisations lack a structured intermediate step between strategy and the first build that brings use case, data, solution and ROI to a decision-ready depth.
4 phases, 4 gates — you decide at every transition.
In the kickoff with the department and IT we sharpen the goal, affected users and process context. We define measurable success criteria as well as in- and out-of-scope, and record everything in a use case profile.
We check data availability, quality, access paths and source systems, and assess the technical feasibility as well as legal restrictions (GDPR/EU AI Act reference) using a structured grid.
We sketch one to two architecture options with a make-or-buy classification, a well-founded tool/model choice (RAG vs. API vs. fine-tuning), M365 integration as well as guardrails and labelling.
We lay down a rough economic viability logic with effort and value ranges and a payback corridor, classify risks and EU AI Act relevance, and formulate a go/no-go recommendation with an implementation roadmap.
Compact profile of the use case: goal, affected users, process context, in-/out-of-scope and measurable success criteria.
Structured assessment grid on data availability, quality, access, technical feasibility and legal restrictions.
Solution draft with 1–2 architecture options, make/buy classification, tool/model choice (RAG/API/fine-tuning) and M365 reference.
Traceable effort and value consideration with ranges and a payback corridor — deliberately without savings guarantees.
Risk overview and EU AI Act/GDPR-oriented classification of the use case with pointers to required actions.
Well-founded decision recommendation with options as well as a concrete roadmap for the next implementation step.
The base package stands on its own. Optional modules dock on now or later — you decide how far you go.
The basic lab brings exactly one prioritised use case to decision readiness; this module includes a second, closely scoped use case in the same run. Joint appointments and grids are shared, so the second use case works out cheaper than a separate lab.
If you initially only need one building block, we sharpen — in a moderated workshop (0.5–1 day) — either the use case profile, the architecture and make-or-buy classification, or a data quick check. This is deliberately not a complete feasibility and economic viability package and does not deliver a robust go/no-go recommendation.
If the recommendation is "go", we subsequently scope the concrete implementation: rough backlog cut, sprint-0 preparation and setup for the MVP build. The module prepares the implementation but is not itself a build — that happens in the AI Agent/Knowledge Bot MVP or in the Pilot Support.
Credit: If you directly commission a subsequent MVP or a pilot support engagement, we credit the fee for the Use Case Lab proportionally.
Note: not legal advice. Content with a legal dimension (e.g. EU AI Act, GDPR, ISO/IEC 42001) is professional orientation, not legal counsel.
You receive a clear, individual proposal before any engagement. Under § 19 UStG no VAT is charged; any ancillary costs (e.g. model/hosting/API fees, travel) are not included.
Next step
Let us clarify in a free intro call whether this offer fits your situation — honestly and without sales pressure.As a follow-up we then recommend AI Agent / Knowledge Bot MVP.
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