Blog Archives

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

Building Your Information Shopping Mall – A Semantic Layer Guide

Imagine your organization’s data as a vast collection of goods scattered across countless individual stores, each with its own layout and labeling system. Finding exactly what you need can feel like an endless, frustrating search. This is where a semantic … Continue reading

The Evolution of Knowledge Management & Organizational Roles: Integrating KM, Data Management, and Enterprise AI through a Semantic Layer

On June 23, 2025, at the Knowledge Summit Dublin, Lulit Tesfaye and Jess DeMay presented “The Evolution of Knowledge Management (KM) & Organizational Roles: Integrating KM, Data Management, and Enterprise AI through a Semantic Layer.” The session examined how KM … Continue reading

Semantic Layer for Content Discovery, Personalization, and AI Readiness

A professional association needed to improve their members’ content experiences. With tens of thousands of content assets published across 50 different websites and 5 disparate content management systems (CMSes), they struggled to coordinate a content strategy and improve content discovery. They could not keep up with the demands of managing content … Continue reading

Semantic Layer Maturity Framework Series: Taxonomy

Taxonomy is foundational to the Semantic Layer. A taxonomy establishes the essential semantic building blocks upon which everything else is built, starting by standardizing naming conventions and ensuring consistent terminology. From there, taxonomy concepts are enriched with additional context, such … Continue reading

Graph Analytics in the Semantic Layer: Architectural Framework for Knowledge Intelligence

Introduction As enterprises accelerate AI adoption, the semantic layer has become essential for unifying siloed data and delivering actionable, contextualized insights. Graph analytics plays a pivotal role within this architecture, serving as the analytical engine that reveals patterns and relationships … Continue reading