Retrieval-Augmented Generation (RAG) has unlocked new capabilities for large language models (LLMs) by providing them with external context. But in real-world settings, many RAG systems still struggle—relying on static pipelines and vector-only retrieval that often fall short when queries are complex, multi-step, or domain-specific.
This talk explores how knowledge graphs can address these limitations, evolving RAG into a more structured and semantically aware system. We'll introduce Graph RAG, a practical approach that incorporates entities, relationships, and provenance to improve retrieval quality, enable traceable reasoning, and provide fine-grained control over what’s retrieved—and why.
Building on this foundation, we’ll share our work on extending toward agentic RAG: LLM-powered agents that use graph-native reasoning and declarative logic to plan and execute multi-step workflows. These systems go beyond passive retrieval and toward active problem-solving across structured data.
You’ll leave with practical patterns, architecture ideas, and an understanding of how to build retrieval workflows that are robust, intelligent, and ready for scale.
What you’ll learn:
- Where traditional RAG architectures break down in complex domains
- How Graph RAG leverages semantic context for better retrieval and reasoning
- How Graph RAG can leverage agentic workflows to enable multi-step workflows grounded in structured data
- Design patterns and architectures that you can apply today with graph-native systems
- How to build AI systems that go beyond chatbots and toward robust, explainable automation
Speaker
Cassie Shum
Vice President of Field Engineering @RelationalAI, Previously @Thoughtworks
Based in New York, Cassie is the VP of Field Engineering of RelationalAI and leads a team to bring a cloud-native knowledge graph data management system to power the next generation of intelligent data applications. She was the Head and Technical Director for Architecture and Development in North America. As a software engineer and architect, she had spent the last 12+ years at Thoughtworks focusing on building highly scalable and resilient architectures including event driven systems and microservices on cloud based technologies. She had been focused on a wide range of technologies with an emphasis on cloud, mobile and software delivery excellence. She was a member of the ThoughtWorks Technology Advisory Board and contributed to the creation of the ThoughtWorks Technology Radar.
Cassie had also been involved in growing not only organizations in the delivery practices and technical strategy, but also the next generation of technologists. Some of her passions include advocating for women in technology and public speaking. She is also involved in promoting more female speakers in technology.
