S1E5: The GraphRAG Curator in interview with Aaron Philipp

Aaron Philipp, founder of VisibleARC and former partner at Ernst & Young, brings decades of cybersecurity and graph expertise to the challenge of implementing agentic AI in an enterprise security context. His company uses diffusion models to create synthetic network environments—in factories, hospitals, IoT systems—that serve as sophisticated decoys for large multinationals and government organizations.

I first met Aaron when both of us were at PwC in the 2010s. Aaron back then was a director in the firm’s cybersecurity practice. He was using innovative, large scale graph database technology for analytics back then. 

To this day, Aaron’s still using graphs in creative ways in the solutions he designs. In this episode, he notes that while large language models (LLMs) operate in Euclidean space—discrete, linear, and grid-oriented—cybersecurity threats exist in non-Euclidean problem spaces. Graph structures naturally capture network architectures, risk pools, and threat patterns in ways transformers cannot. 

During the interview, Aaron notes that 91% of enterprise AI deployments fail. The primary culprit isn't the technology itself, but an inadequate data foundation. 

Aaron’s diagnosis here is that companies lack proper data strategies, process understanding, and the overall data maturity necessary to harness the power of generative and agentic AI. He draws parallels to the big data era of the 2010s and the typical data lake as data swamp, noting that without structure, "if you throw a RAG system at a SharePoint site with unstructured documents, you've created a hallucination machine."

Interestingly, Aaron points out that organizations that invested in robotic process automation (RPA) will likely be surprisingly well-positioned for agentic AI. Even if RPA implementations were "failures" in terms of automation goals, the process documentation and organizational understanding gained provide critical context that can accelerate AI agent deployment and significantly reduce costs.

So many insights like these in the interview that follows. Hope you enjoy it.

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