| Date: | 03 September 2026, 16:00-18:00 (CEST) | Price: | Free (for eligible participants) | |
| Format: | AI:AT Webinar, ONLINE (Zoom) | Target audience: | Industry, public admin, academia | |
| Language: | English | Organizer: | AI:AT |
Learn how to supercharge AI agents with structured knowledge bases and knowledge graphs. This training explores how to build, connect, and query knowledge representations that give LLM-based agents reliable, up-to-date, and domain-specific information for smarter decision-making.
LLMs are powerful, but on their own they often struggle with domain-specific, up-to-date, or structured knowledge - leading to hallucinations, unreliable and contextually irrelevant outputs. This training addresses a key challenge in building effective AI agents: equipping them with external knowledge bases that provide accurate, structured, and queryable information. Participants will explore how knowledge graphs and knowledge bases can serve as a persistent "memory" and factual backbone for LLM-based agents, enabling them to reason over real-world entities, relationships, and domain-specific facts rather than relying solely on pre-trained general knowledge.
The session covers the spectrum from lightweight approaches - such as connecting agents to curated wikis and document stores via Retrieval-Augmented Generation (RAG) - to more advanced architectures that integrate knowledge graphs with graph-based querying (e.g., SPARQL, Cypher) to enable structured reasoning. Participants will learn how domain knowledge is modelled as a graph, populate it from various data sources, and integrate it with AI agents so that the agent can look up facts, traverse relationships, and ground its responses in verified information. Whether you are building internal company knowledge assistants, domain-specific Q&A systems, or AI agents to work with your Personal Knowledge Graph, this training provides the practical patterns to get started.
Target audience
The webinar is aimed at everyone who wants to understand knowledge graphs and how to combine them with AI agents.
Attendance is open and free of charge for all participants from academia, industry, and public administration from EU and/or EuroHPC JU member countries.
Entry level & prerequisites
Basic - no prior experience required.
Agenda
- Welcome & Introduction
- Knowledge Graphs: Concepts, Entities & Relationships
- AI Agents with Knowledge Bases: Connecting LLMs to Obsidian-style Wikis & Document Stores
- Break
- AI Agents with Knowledge Graphs: Traversal, Multi-hop Queries & Grounded Reasoning
- Choosing the Right Architecture for Your Use Case
- Questions & Discussion
Speakers
Daniel Dobriy (WU Vienna, Bilateral AI Cluster of Excellence, Dobriy AI GmbH)
Daniel Dobriy is an AI researcher and lecturer at the Institute for Data, Process and Knowledge Management at WU Vienna. His work bridges symbolic AI, graph-based machine learning, and applications in public governance, finance, education, and scientific discovery. He is a Research Fellow at the Bilateral AI Cluster of Excellence, an industry leader in the GOBLIN COST Action, and an active member of the W3C RDF and SPARQL Working Group. Daniel Dobriy is certified in Value-based Engineering ISO 24748-7000, is a member of ASAI, ÖCG, ACM and ACL, chairs RAGE-KG and serves on programme committees of leading international venues including The Web Conference, ISWC (International Semantic Web Conference), ESWC, K-CAP, HICSS, SEMANTiCS as well as IJCKG. Daniel Dobriy is also the managing director of Dobriy AI GmbH (dobriy.ai).
Registration
Registration is required, the link to the registration form can be found on the top of this page in the menu on the left. Please register with your official institutional email address to prove your affiliation.
You will get the Zoom link in the automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders). We will also send 1–2 reminders before the webinar.
Please do not hesitate to contact us at training@ai-at.eu if you have any questions.
Organizers
This webinar is organized by AI Factory Austria AI:AT.
Acknowledgements
AI Factory Austria AI:AT has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101253078. The JU receives support from the Horizon Europe Programm of the European Union and Austria (BMIMI / FFG).
