Uploaded August 2026 | Updated September 2026, 2 weeks ago
In this interview from GraphTalk, Chad Cloes, senior software staff engineer at Intuit, joins theCUBE's John Furrier to discuss how knowledge graphs are becoming the contextual layer that turns commodity large language models into differentiable, explainable enterprise AI systems. Cloes details how Intuit's Security Knowledge and Insights Platform replaced sprawling SQL joins with native graph relationships, treating connections as first-class citizens rather than afterthoughts. He explains how this contextualization directly powers security attribution and explainability, giving the company auditable lineage for compliance needs such as SOX and IRS 7216 requirements around tax data.
The conversation also explores how Intuit operationalized graph technology in production using Neo4j Aura, driving mean time to remediate from days down to seconds. Cloes describes automated systems that continuously query the graph and escalate findings, with humans remaining in the loop for judgment calls and sensitive cases. He breaks down how a GraphQL API built on top of the platform enabled the team to stand up an MCP server within minutes, letting developers ask natural-language questions about unfamiliar projects and instantly surface context spanning repositories, cloud assets and ownership. Cloes also touches on how graphs abstract teams from underlying tools like Wiz, Databricks and S3, insulating systems from vendor churn. From replacing thousand-line SQL joins to powering agentic developer workflows, Cloes makes the case that graph technology is quickly becoming a prerequisite for reliable, production-grade enterprise AI.
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00:00 - Intro
00:05 - Intuit's Graph Journey: From Open Source to AI-Driven Security
03:29 - Enhancing Insights: Security Attribution and Explainable Graph Science
06:05 - Enhancing AI Systems: Reliability, Optimization, and Rapid Response
09:34 - Integrating and Contextualizing Data for Developers
13:11 - Empowering Data: Graphs and AI Alignment
15:18 - Integrating Graphs and Data Ecosystems: Shaping the Future of AI
#theCUBE #Neo4jGraphTalk #theCUBEresearch #Intuit #KnowledgeGraphs #AI #EnterpriseAI
In this interview from GraphTalk, Chad Cloes, senior software staff engineer at Intuit, joins theCUBE's John Furrier to discuss how knowledge graphs are becoming the contextual layer that turns commodity large language models into differentiable, explainable enterprise AI systems. Cloes details how Intuit's Security Knowledge and Insights Platform replaced sprawling SQL joins with native graph relationships, treating connections as first-class citizens rather than afterthoughts. He explains how this contextualization directly powers security attribution and explainability, giving the company auditable lineage for compliance needs such as SOX and IRS 7216 requirements around tax data.
The conversation also explores how Intuit operationalized graph technology in production using Neo4j Aura, driving mean time to remediate from days down to seconds. Cloes describes automated systems that continuously query the graph and escalate findings, with humans remaining in the loop for judgment calls and sensitive cases. He breaks down how a GraphQL API built on top of the platform enabled the team to stand up an MCP server within minutes, letting developers ask natural-language questions about unfamiliar projects and instantly surface context spanning repositories, cloud assets and ownership. Cloes also touches on how graphs abstract teams from underlying tools like Wiz, Databricks and S3, insulating systems from vendor churn. From replacing thousand-line SQL joins to powering agentic developer workflows, Cloes makes the case that graph technology is quickly becoming a prerequisite for reliable, production-grade enterprise AI.
Find more SiliconANGLE news and analysis siliconangle.com
Follow theCUBE's wall-to-wall event coverage siliconangle.com/events
Learn about the latest theCUBE events thecube.net
00:00 - Intro
00:05 - Intuit's Graph Journey: From Open Source to AI-Driven Security
03:29 - Enhancing Insights: Security Attribution and Explainable Graph Science
06:05 - Enhancing AI Systems: Reliability, Optimization, and Rapid Response
09:34 - Integrating and Contextualizing Data for Developers
13:11 - Empowering Data: Graphs and AI Alignment
15:18 - Integrating Graphs and Data Ecosystems: Shaping the Future of AI
#theCUBE #Neo4jGraphTalk #theCUBEresearch #Intuit #KnowledgeGraphs #AI #EnterpriseAI
