Knowledge Cast by Enterprise Knowledge
Sep 24, 2026 · 16 min · 10 segments
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Karthikeyan Palanisamy, Knowledge Management Architect at ASML and speaker at this year's Semantic Layer Symposium…
Karthikeyan PalanisamyGuest
Lulit TesfayeHost
And you know, um, why I have, I have been, uh, uh, calling out the fact that you're really focused on the capture of knowledge.
And, you know, we talk about with, uh, many of our... and I think, uh, organizations that we talk to, there is kind of the shift to the semantic models, uh, but more from the bottom up, from the data side as a data model, whereas we are seeing this traditional KM challenge still persist, especially in the age of context for AI, which is capturing knowledge.
Uh, and, uh, the, the whole point of this KCS model is being able to extract and capture knowledge, uh, in a way, uh, embedded within the operational existence of the organization.
Um, so in light of that, um, you know, especially, uh, there's a lot of talk right now about AI, how, you know, knowledge graphs, ontologies, uh, and semantic layer, the framework provides this context to make it machine readable for AI, which all sounds really impressive, uh, right? But, uh, if you're a leader, it is a very challenging, uh, place to be right now.
There's a lot of noise in this space, uh, and you're coming at it from the someone who's doing this on the ground.
So a simple question, maybe not so simple is: Does it actually work? I think that's what, uh, everybody's has, uh, top of mind these days.
And you know, um, why I have, I have been, uh, uh, calling out the fact that you're really focused on the capture of knowledge.
And, you know, we talk about with, uh, many of our... and I think, uh, organizations that we talk to, there is kind of the shift to the semantic models, uh, but more from the bottom up, from the data side as a data model, whereas we are seeing this traditional KM challenge still persist, especially in the age of context for AI, which is capturing knowledge.
Uh, and, uh, the, the whole point of this KCS model is being able to extract and capture knowledge, uh, in a way, uh, embedded within the operational existence of the organization.
Um, so in light of that, um, you know, especially, uh, there's a lot of talk right now about AI, how, you know, knowledge graphs, ontologies, uh, and semantic layer, the framework provides this context to make it machine readable for AI, which all sounds really impressive, uh, right? But, uh, if you're a leader, it is a very challenging, uh, place to be right now.
There's a lot of noise in this space, uh, and you're coming at it from the someone who's doing this on the ground.
So a simple question, maybe not so simple is: Does it actually work? I think that's what, uh, everybody's has, uh, top of mind these days.
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