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Content related to How to Ensure Your Data is AI Ready

How to Fill Your Knowledge Gaps to Ensure You’re AI-Ready

“If only our company knew what our company knows” has been a longstanding lament for leaders: organizations are prevented from mobilizing their knowledge and capabilities towards their strategic priorities. Similarly, being able to locate knowledge gaps in the organization, whether … Continue reading

Top Ways to Get Your Content and Data Ready for AI

As artificial intelligence has quickly moved from science fiction, to pervasive internet reality, and now to standard corporate solutions, we consistently get the question, “How do I ensure my organization’s content and data are ready for AI?” Pointing your organization’s … Continue reading

Knowledge Cast – Ben Clinch, Chief Data Officer & Partner at Ortecha – Semantic Layer Symposium Series

Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Ben Clinch, Chief Data Officer and Partner at Ortecha and Regional Lead Trainer for the EDM Council (EMEA/India). He is a sought-after public speaker and thought leader in … Continue reading

When Should You Use An AI Agent? Part One: Understanding the Components and Organizational Foundations for AI Readiness

It’s been recognized for far too long that organizations spend as much as 30-40% of their time searching for or recreating information. Now, imagine a dedicated analyst who doesn’t just look for or analyze data for you but also roams … Continue reading

Webinar: Semantic Graphs in Action – Bridging LPG and RDF Frameworks

As organizations increasingly prioritize linked data capabilities to connect information across the enterprise, selecting the right graph framework to leverage has become more important than ever. In this webinar, graph technology experts from Enterprise Knowledge Elliott Risch, James Egan, David … Continue reading

Auto-Classification for the Enterprise: When to Use AI vs. Semantic Models

Auto-classification is a valuable process for adding context to unstructured content. Nominally speaking, some practitioners distinguish between auto-classification (placing content into pre-defined categories from a taxonomy) and auto-tagging (assigning unstructured keywords or metadata, sometimes generated without a taxonomy). In this article, I use ‘auto-classification’ in the broader sense, encompassing both approaches. Continue reading

LLM Solutions PoC to Production: From RAGs to Riches (Part 1)

In the past year, many of the organizations EK has partnered with have been developing Large Language Model (LLM) based Proof-of-Concepts (PoCs). These projects are often pushed for by an enthusiastic IT Team, or internal initiative – with the low … Continue reading

Maturing Data Processes at a Decentralized Federal Organization

A large government agency sought EK’s help in addressing significant data management challenges they were facing. The agency had a decentralized organizational structure and a complex technical ecosystem, which created unique challenges for remote employees in finding, accessing, and sharing critical data at the time of need. These challenges resulted … Continue reading