Connect data and systems: open up sources, prepare data, define interfaces and system boundaries
AI implementation. One system, cleanly handed over.
I develop and integrate one clearly verified use case. I define the data sources and interfaces; together, we set the quality criteria up front. The result is an accepted system your team can run on its own.
- Duration
- 4–10 weeks
- Pricing model
- Project-based · on request
What I build and hand over
Develop an automation flow, internal AI assistant or RAG system and integrate it into the real process
Test, accept and hand over the system: test catalog, documentation and training
When WDC fits. What you leave with.
When this service fits
- The use case has been verified technically and commercially. Implementation is missing.
- Recurring data or knowledge work ties up skilled staff.
- A prototype exists. Integration, quality assurance and a path into operations are missing.
- Internal knowledge sits in documents and heads. It is hard to access in daily work.
What you have after the project
- A working system in the real process — tested and accepted against defined criteria
- Technical documentation and training for independent operation
- A clear basis for handover, operation and focused expansion
What a project looks like in practice
Scattered knowledge. One verifiable assistant.
An engineering team answers recurring technical questions manually. Senior engineers become the bottleneck.
Specifications, standards and experience sit across PDFs, wikis and personal notes. Reliable access is missing in daily work.
I define the usage scenario, data sources and quality criteria with the team, then develop and integrate the assistant and test it against an agreed test catalog.
Recurring questions are answered with sources. Difficult cases escalate to senior engineers. After acceptance, documentation and training, the team runs the system itself.
Verify first or build now?
Describe your case and I'll tell you whether to verify first, build now or deliberately not invest.