Contents
Imagine a library with endless shelves full of books - books without titles, without categories and indexes. And now imagine that you are trying to find a specific fact in this labyrinth. Frustrating, isn't it? This is the reality that many companies face today with their legacy data. Technical documents that have been created over decades are not organized and with missing metadata. The challenge? Providing accurate, useful information to the users who need it tailored to their task and situation of use. In our presentation, we will demonstrate how we address this challenge using AI and Knowledge Graphs. Using advanced data processing and knowledge modeling techniques we can parse, structure, chunk and organize unstructured legacy content, making it searchable and contextually relevant. By integrating this data into an existing knowledge base within an information system, we enable its retrieval, update and extension. This helps organizations to overcome the limitations of legacy data. Join us to explore how AI is breathing new life into legacy data.
Takeaways
Is to understand the process of creating a robust knowledge base that integrates AI-enriched legacy data, allowing it to be easily retrieved, extended, and updated.