Syntes AI Digital Twin Agentic Platform with Graph Data Model

Session Track: Data Intelligence

Session Time: 12:45 am - 01:00 am November 7

Session description

As AI systems increasingly interact with complex, dynamic real-world environments, developers face the challenge of creating intelligent agents that can model, reason, and act with autonomy and contextual awareness. The Syntes AI Digital Twin Agentic Platform addresses this by leveraging a graph-based data model (with Neo4J database at the core) to represent entities, relationships, and behaviors within adaptive digital twins. In this session, attendees will be introduced to how graph databases underpin the architecture of agentic systems, enabling fine-grained semantic memory, causal reasoning, and multi-agent collaboration. Through live demonstrations and real-world case studies, you will learn how the platform orchestrates LLMs with graph-structured context, integrates temporal event modeling, and uses agents as dynamic, learning-based digital twins. By the end of the session, you will understand how to build and deploy intelligent agentic systems that evolve over time and drive real impact in applications ranging from R&D automation to decision intelligence.