Enterprise Data, Knowledge Graphs, Search and AI
How do these technologies fit together?
This webinar will explore the intersection of knowledge graphs, search and applied AI. The speakers will discuss how these technologies can be used together to solve complex business problems with enterprise data, such as:
- Improving Findability
- End-to-end smart data integration using Knowledge Graphs and AI
- Knowledge Management and recommender systems
- Assisted (automated and augmented [AI]) data management
- Data Mesh
- Making better decisions
Don’t miss this opportunity to see how emerging technologies, will serve and improve data quality, data integration and findability in large enterprises.
The capabilities used, encompass semantic tools (PoolParty), graph databases (GraphDB), search technologies (Findwise i3) and applied AI/ML (including LLM exploration).
This webinar will take place online, 3:00 – 4:00 PM CET.
Your personal link to the webinar will be sent out in the confirmation e-mail.
Speakers
Experienced consultant, with 34 years as information professional and researcher. His focus is knowledge management, knowledge engineering, information management and information architecture. He has extensive experience with semantic and search based technologies, including emerging applied AI.
Krzysztof is building AI based info retrieval systems and providing search engines based on Elastic stack. His experience includes business processes analysis and optimisation, including ISO IT Management Systems, like IT Service Management, IT Asset Management, or Information Security Management.
Emil is leading our connected data team, focused on coordinating partnerships and identifying customer’s information challenges. He is experienced in bridging the gap between the capabilities of search, i3- and knowledge graph technology and value creating activities in customers’ daily operations.
Contact us
Principal Information Architect
Speakers
Principal Information Architect
Senior Solution Architect & Developer
Business Developer