We structure your data and give it meaning.
Technical content is only understandable if its meaning is clear. This has not changed until today, and the topic has expanded into the semantic web. Information and the relationships between them are only comprehensible, easy to find and processable by humans as well as machines or algorithms if they are semantically marked (according to their meaning).
Together with you, we develop semantic models, ranging from structural models for texts contained in topics to error codes, which we integrate into your service portal via knowledge graphs in order to automatically find suitable content for troubleshooting via metadata. In doing so, we are guided by your goals and processes. We take care not to bend existing systems, but to put semantics on top of your data as a layer of its own. In doing so, we stick to standards and do not reinvent the wheel.