06 / Services
Engineering digitisation & AI
I turn technical documentation and knowledge into verifiable systems that accelerate search, configuration and quotation.
Explore the capability →01 / The problem
Problems
- Specifications, variants and product rules are scattered across PDFs, technical sheets, price lists and the memory of a few people.
- Configuration or quotation requires manually searching and rereading the same documentation every time.
- An AI answer may sound correct, but without validated data and a verifiable source it cannot become a technical decision.
02 / The solution
What
I start from PDFs, technical sheets, specifications, price lists, rules and distributed knowledge. I structure the domain, connect data and sources, and build tools that can retrieve information, support configuration, prepare quotations or assist decisions while keeping every answer traceable to its source.
What I build
- Pipelines that extract, normalise and validate information from technical documentation.
- Domain knowledge systems connecting products, variants, rules, specifications and sources.
- Assistants and workflows for technical search, configuration, quotation and decision support.
03 / What you get
Deliverables
- 01
A documented model of the technical domain: entities, relationships, rules and sources.
- 02
A usable system for querying or applying that knowledge to a real use case.
- 03
Traceability from an answer or decision back to the data and original document.
05 / How I work
Process
- 01
Understand — Domain, people, documents, questions and decisions to support.
- 02
Structure — Entities, relationships, rules, sources and validation criteria.
- 03
Build — Extraction, knowledge layer, interface, AI and operational workflow.
- 04
Validate — Real cases, sources, anomalies, answer quality and decisions.
Have something that needs to become real?
Tell me the starting point: a problem, an idea, a process or a brand. You don’t need a perfect brief — just know what needs to change.