Practice 01 of 04
AI Strategy and Transformation
Where AI pays off first, and the roadmap and operating model to scale it.
We work with your leadership and IT teams to decide which workflows get AI first and what each one has to prove. The result is a ranked roadmap and an operating model your teams can build from.
AI Strategy and Transformation
What the work covers
Opportunity map
A ranked list of candidate workflows across your functions, scored on the hours they take today and the risk if an agent gets them wrong.
Readiness assessment
How ready your data and access controls are today, and what has to change before the first agent goes live.
AI readiness checkRoadmap
The order of builds and what each one depends on. Every build on the roadmap carries the acceptance criteria it has to meet.
Operating model and governance
Who owns each agent and who approves its output. We also set how models are evaluated and how the program meets the EU AI Act.
AI governanceAdoption
Training and change plans for the teams who will work with the agents, including Microsoft 365 Copilot rollouts.
Microsoft 365 Copilot deploymentAI program as a service
We can also run the whole program beside your IT team, from strategy and governance to the agents your teams use.
AI as a ServiceProof
Work we can show you
Since 2014
200+
Production deployments on AI and the Microsoft platform since 2014, for companies including Bayer, Takeda, Rockwell Automation and Burckhardt Compression.
Founded in Germany
2014
Microsoft partner since 2015. We build on Azure and AWS, with teams in Texas and Munich.
How an engagement starts
From the first call to a workflow in daily use.
Every engagement starts with one scoped workflow and a written definition of done. Commercial terms are set in the statement of work.
- First call
A conversation with our team
You tell us about the program or the workflow you have in mind, the systems involved and who checks the work today.
- Scoping
One scoped workflow
We agree which workflow comes first and what done looks like for it: the inputs, the outputs, the accuracy it must reach and where a person approves the result.
- Before the build
A written definition of done
The acceptance criteria go into the statement of work with the deliverables and the commercial terms. Nothing is built before both sides sign.
- Delivery
Build, then run or hand over
We build in your environment and test against the criteria you signed. Then we run the workflow for you, or your own team takes it over with the documentation.
Go deeper
Related pages
- AI readiness checkEight questions, a weighted score and the blockers to clear first.
- AI as a ServiceYour AI program, run with your IT team.
- AI governanceThe governance stack, installed as working systems.
- The enterprise AI pilot paradoxWhy pilots multiply while production stalls.
- How we engageAdvisory, build, run and outcome-linked terms.
Planning an AI program?
Talk to the team that builds it and runs it after launch.
- Built to SOC 2, HIPAA and GDPR standards
- EU AI Act-aligned delivery
- Microsoft Solutions Partner