Content related to How Leveraging Existing Taxonomies Can Jumpstart Ontology Design
From Risk to Readiness: Anatomy of an AI-Ready Knowledge Asset
The hidden risk in your AI investment isn’t the technology; it’s the content. The core issue is that humans and AI systems process information differently: humans infer context and build on an ever-expanding web of knowledge; AI systems require explicit … Continue reading
A Practical Guide to an Intranet Remodel: Small Taxonomy Wins for a Big Impact
The world of knowledge management is moving at a fast pace and it is challenging to keep up with trends that often demand investing in the latest tooling to solve increasingly complex semantic challenges. However, for many organizations, particularly non-profits, … Continue reading
Knowledge Cast – Wael Taha, Vice President of Enterprise Architecture at Brown Brothers Harriman
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Wael Taha, VP of Enterprise Architecture at Brown Brothers Harriman. Over the past 12 years, Wael has dedicated his career to architecting D&A solutions and directing D&A professionals … Continue reading
Ontology and Knowledge Graph in the Age of AI and Agents
As organizations accelerate investments in AI, semantic data models, advanced analytics, and agentic transformation, lots of jargon gets thrown around, and this sometimes results in confusion about how data driven systems work. In the realm of semantic layers, one of … Continue reading
Knowledge Cast – Bridging Knowledge, Data, and AI by Zach Wahl, Joe Hilger, and Lulit Tesfaye
In this special episode of Knowledge Cast, Zach, Joe, and Lulit pass the mic to Senzing‘s Paco Nathan, who interviews them about their new book Bridging Knowledge, Data, and AI: Harnessing the Semantic Layer Framework to Drive Intelligence. Paco guides … Continue reading
Why AI Projects Fail Without a Common Language: The Case for Taxonomy Standards
As organizations rush to adopt AI solutions and technologies, the necessary structures to support such solutions are often overlooked. Gartner predicts that by 2026, 63% of organizations will not have the right data management practices for AI. This gap shows … Continue reading
Knowledge Cast – Lasse Andresen, Founder & CEO of IndyKite
Enterprise Knowledge COO Joe Hilger speaks with Lasse Andresen, founder and CEO of IndyKite Inc., the first system of intelligence built on a live context graph. The result is agentic AI that can operate across platforms with precision and deliver … Continue reading
How to Scale a Semantic Layer with Interoperable Ontologies
A Semantic Layer is the framework for connecting data from multiple sources and formats in both a human- and machine-readable way that enables organizations to understand the meaning of their data, extract contextualized information, and discover new insights. A key … Continue reading
A Practical Guide to a Taxonomy Remodel
For anyone who has undertaken any form of home remodel or loves to watch television shows featuring them, the general phases of a home renovation are familiar: visualizing the target state of the remodeled home, carrying out structural work, demolition, … Continue reading
Taxonomies vs. Ontologies for Enabling AI-Readiness
AI solutions need to be grounded in an organization’s context. It is difficult to reliably distill context from the entirety of an organization’s knowledge assets, including facts, documents, datasets, and other structured records. Without a specific directive on what matters … Continue reading