Typical starting point
We often encounter the following picture: initial internal AI pilots with ChatGPT plugins remained disappointing – a lack of domain knowledge, no audit trail, nagging data-protection concerns. At the same time, growing pressure from ticket volume and EU AI Act requirements that make every productive AI deployment subject to documentation obligations.
The typical brief we receive: pilot two concrete AI use cases that deliver immediate impact while remaining audit-ready.
How we typically proceed
Ten weeks, five phases – a senior consultant together with an AI specialist:
- Use-case workshop (weeks 1–2) – with QA, Compliance, Data Protection and Architecture – prioritisation by impact and risk.
- Tool selection and data-protection concept (weeks 2–3) – hosting model with EU data residency, clear responsibilities under GDPR and the EU AI Act.
- Pilot 1: Defect triage (weeks 3–6) – LLM-assisted classification and routing of incoming tickets, with human-in-the-loop.
- Pilot 2: Test-data generation (weeks 6–8) – synthetic load-test data, anonymised and auditable.
- Audit documentation and scaling plan (weeks 8–10) – record-keeping under the EU AI Act, a concept for extending to further QA use cases.
Typical impact figures
These are the orders of magnitude we typically see a few months after the end of an engagement in comparable mandates:
Range depends on data availability and use-case selection. We establish reliable expected values for your case in the Quick-Check.
Typical engagement framework
