Giving Enterprise AI the Context It Needs With Orange Logic
Tech Talks Daily

Giving Enterprise AI the Context It Needs With Orange Logic

B2Upper-intermediateSeptember 27, 202621 min

Why do increasingly capable AI models struggle to produce reliable answers inside large organizations? In this episode of Tech Talks Daily, I speak with Misti Vogt, SVP of Engagement at Orange Logic. Her career spans military intelligence, data science, and enterprise content technology, and she also teaches in the DAM and AI program at Rutgers University. That combination gives her an unusually practical perspective on how machines interpret information and why business meaning cannot be assumed. Misti argues that enterprise AI reliability depends on the context surrounding company data. A model may be technically impressive...

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Why can an increasingly capable AI model still produce unreliable answers inside a business,

?

Well, in today's episode, I'm going to be speaking with the SVP of Engagement at Orange

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0:00

Why can an increasingly capable AI model still produce unreliable answers inside a business, even though it has more data than ever to refer to? Well, in today's episode, I'm going to be speaking with the SVP of Engagement at Orange Logic.

0:22

Together, we're going to talk about the missing layer between enterprise data and dependable AI. My guess brings vast experience spanning everything from military intelligence, data science, enterprise content technology, and teaching Digital Asset Management, or DAM as it's often known in the industry, and AI at Rutgers University. But today she's

0:49

going to explain why models need business context. By that we include everything from metadata, relationships, rights, rules and intent before they can reason usefully over company information. And I also want to bust a few myths today and learn how digital asset management is becoming part of the data foundation

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