Ai+ Training

In my decade following the graph technology landscape, I've never witnessed such rapid transformation as we're seeing now. The intersection of AI, new frameworks, and evolving use cases has created a perfect storm of innovation that's reshaping how we think about connected data. In this talk, we'll dive into recent market shifts and graph technology innovations that are changing the way organizations can now tackle and incorporate more connected intelligence.
In the last year, we've seen graph awareness explode, but adoption remains with very focused production uses rather than broad application. In addition, everyone is looking to make developing and using graphs more intuitive, from query languages and developer tools to dashboarding and graph BI.
Perhaps most disruptive is how AI and LLMs have fundamentally changed expectations around what's possible with graph technologies:
Knowledge graphs are increasingly serving as critical context for AI systems
Agentic workflows are automating graph creation while also potentially introducing risks of ill-defined graph structures
LLMs are making graphs more human-friendly than ever before
And the industry overall is lowering the barrier to entry for organizations across sectors
In addition, we'll look at how companies are evolving traditional graph database applications towards more specialized frameworks and a mix of different frameworks within a single environment. We'll also explore emerging use cases and applications across industries, examining how legal document processing, manufacturing processes, and digital twins are leveraging graph technologies in novel ways.
We'll also cover emerging innovations like graph-vector hybrid models, multimodal GraphRAG, and temporal graphs. We'll lightly touch on advanced graph concepts like hypergraphs, and neuromorphic approaches that are pushing the boundaries of what's possible.