Most AI initiatives fail before development starts — because the wrong problems are chosen. We run a structured audit of your operations, score every opportunity by ROI and feasibility, and deliver a phased roadmap your leadership and technical teams can act on immediately. No slides. No generalised advice.
Many German enterprises begin AI adoption with a use case in mind — only to discover six months later that the data wasn't ready, the integration was underestimated, or the ROI assumption didn't hold. Our strategy engagement prevents that by working backwards: we start with your workflows, your data infrastructure, and your compliance obligations (including GDPR data residency requirements), then identify where AI genuinely reduces cost, accelerates throughput, or improves decision accuracy.
The output is a working document — not a presentation deck. It contains a prioritised opportunity matrix scored across impact, implementation complexity, and data readiness; specific technology recommendations across open-source and commercial stacks; and a phased 3–18 month roadmap with defined milestones and ownership. It is written to be handed directly to your engineering leads or used as a brief for external vendors.
Structured interviews with stakeholders across operations, IT, and finance. We document every process in scope, map data inputs and outputs, and identify where manual effort, decision latency, or error rates are highest.
Every automation candidate is scored across five dimensions: estimated ROI, data availability, implementation complexity, compliance risk, and time-to-value. Scores are transparent and defensible — not subjective.
We assess data quality, volume, labelling status, access controls, and storage architecture. You receive a clear view of which initiatives can start now and which require data preparation first.
Build vs. buy analysis covering LLM providers, vector databases, MLOps platforms, and integration tooling. Recommendations account for your existing infrastructure, team skills, and total cost of ownership.
A sequenced 3–18 month plan with initiative owners, dependencies, success metrics, and budget estimates. Designed to be handed to an engineering team and executed without further interpretation.
A concise summary document for leadership alignment — connecting each AI initiative to a specific business outcome with projected impact. Structured for presentation to boards or steering committees.
Structured interviews with 4–8 stakeholders across business and technical functions. We review existing system architecture, data flows, and documentation. No assumptions are carried into the analysis. Deliverable: annotated process map.
Each identified opportunity is modelled against your specific cost structure and operational metrics. We run ROI projections, assess regulatory exposure under GDPR and EU AI Act considerations, and rank initiatives by expected business impact per implementation euro.
We present findings in a working session with your leadership team — walking through every recommendation, handling objections, and aligning on priorities. You receive the complete document set the same day.
30 minutes is enough to identify whether your operations have high-value AI opportunities and what it would realistically take to capture them. We'll come prepared with specific questions about your sector and processes — you leave with concrete next steps regardless of whether we work together.
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