Knowledge Graphs

Knowledge graphs (KG) as a knowledge base organize data from different sources as a network of real-world objects - such as places, people, events and situations - and illustrate the relationships between them.

They capture the meaning and context behind the data and can reveal insights and connections that would otherwise be difficult to find. They enable the exchange of existing knowledge between humans and machines and provide an ideal basis for advanced AI algorithms. The structured database with validated knowledg improves the results of large language models (LLMs), for example, and at the same time benefits from modern AI methods such as machine processing of natural language in their construction.

Knowledge graphs not only form the basis for question-answer and search systems, but also for automated decision-making by software agents. They bring together information from different data sources and can be used in organisations to avoid manual data collection and integration, thus supporting decision making.

We support you in transforming your data into a knowledge graph that represents the meaning and relationships of the data as a network and thus enables modern algorithms to access the individual secured data of your organization.

Knowledge graphs are also the basis for Neuro-Symbolic AI, which combines the advantages of symbolic and neural AI.