Building a Knowledge Graph Context Layer for Industrial A: Bob van de Kuilen - Director, Thred
AI in ManufacturingShow Notes
Context isn't static.
It's a living layer of knowledge built through problem-solving, conversation, and understanding the complex relationships on the factory floor.
This simple truth is often overlooked in industrial data strategies.
We’ve been conditioned to believe that context can be predefined; baked into standards, taxonomies, and hierarchies.
But in real-world manufacturing, things change, people think differently, and use cases evolve.
So how can we build this dynamic layer of understanding for industrial AI?
In our latest AI in Manufacturing episode, I spoke with Bob van de Kuilen, Director at Thred, about a more human-centric approach to industrial data contextualisation using Knowledge Graphs.
Thred is a tool that plugs into Ignition Platform, enabling users to visualize their factory assets in a knowledge graph, link related data points, embed domain expertise, and deliver structured, contextualized data to AI and analytics tools.
We discuss:
✅ Why traditional approaches to data context often fail
✅ Knowledge Graphs act as a mind map for data
✅ The practical steps to building context
✅ How this new context layer serves as the perfect foundation for AI agents.
More from AI in Manufacturing
AI Is Reshaping Industrial Software. Who Wins? | Michael Finocchiaro Will AI simply make established industrial software better, or will it fundamentally change which companies dominate the market? In this episode of AI in Manufacturing, I sit down with Michael Finocchiaro, founder of ThreadMoat Intelligence, to explore how AI is reshaping the competitive landscape of industrial technology, where AI-native startups are challenging established vendors, and what the industrial software market could look like over the next five years. We go beyond the competitive landscape to examine how the underlying technology architecture is evolving, from increasingly composable software and AI-driven orchestration to the changing roles of traditional systems like MES and PLM. In this episode, we explore: Why AI-native startups are challenging established industrial software vendors and where incumbents still have an advantage. How AI is changing traditional industrial software categories, including MES, PLM, and manufacturing data platforms. Why composable architectures and AI agents could fundamentally change how industrial systems are integrated and orchestrated. How manufacturers should think about data ownership, interoperability, and vendor lock-in when evaluating emerging technologies. What the industrial software landscape could look like in five years, including the evolving roles of AI agents, knowledge graphs, and human decision-making. Michael brings a broad perspective from tracking industrial technology startups, interviewing founders, and analyzing emerging trends across engineering and manufacturing software. Whether you're building industrial software, investing in emerging technologies, or shaping your organization's manufacturing technology strategy, this conversation offers valuable perspectives on the shifts already underway and what they could mean for the industry. Learn more: Industry40.tv: https://www.industry40.tv
# AI in Manufacturing Podcast
# AI in Manufacturing Podcast — Show Notes ## Episode: Scaling Industrial Intelligence with the I3X Common API
# AI in Manufacturing Podcast: Episode Show Notes
**Podcast Name:** AI in Manufacturing Podcast **Episode Title:** How to Build AI Solutions That Actually Work on the Factory Floor **Guest:** Renan De Villiers, Founder & CEO, OSS Ventures **Host:** Kudzai Manditereza