Lectures
The integration of technical documentation in Product Information Management Systems powered by Knowledge Graphs and LLMs
In the technical documentation domain, the challenge lies not only in managing diverse data but also in making it contextually relevant to business needs. Traditional content management systems often fall short due to their inability to provide meaningful contextual knowledge about related information within the same company. Technical documentation enhanced with knowledge graphs significantly improves decision-making. A knowledge graph-based product information management system can integrate all data sources as a single source of truth. The knowledge graph uses ontologies to structure and interpret data from various sources, including internal and external technical documentation. Business use cases, such as comparing the technical efficiency of internal products with that of competitor products, demonstrate the practical benefits. Integrating generative large language models with knowledge graphs allows for more accurate natural language question answering of business questions.

Unlocking the Potential of Legacy Data with AI and Knowledge Graphs
Sofia Darie, Nikhil Achary. Unlocking the potential of legacy data with AI and Knowledge Graphs. Information Energy, April 2025.

From Legacy Systems to DITA: Case Studies in Successful Migration
Sofia Darie, Karsten Schrempp. From Legacy Systems to DITA: Case Studies in Successful Migration, February 2025.

Product ontologies as backbone for GenAI
Maximilian Gärber, Prof. Dr. Martin Ley. Product ontologies as backbone for GenAI. tcworld, November 2024.
Contact us
Maraike Heim
Head of Marketing
- maraike.heim@pantopix.com
