Blog Archives
3 Common Pain Points in Transitioning from Semantic Strategy to Implementation and How to Avoid Them
At EK, we work with many organizations that are looking to connect, standardize, and enrich knowledge assets (both structured data and unstructured content) for their enterprise through the implementation of a Semantic Layer. While traditionally, Semantic Layer implementation was in … Continue reading
The Unintended Consequences of Artificial Intelligence
Organizations continue to make significant investments in Enterprise AI, bringing Agentic and Generative AI solutions into their own operations and systems, with the goals of improving their operations through automation and machine learning. Within the context of knowledge, data, and … Continue reading
Enterprises, KM, & AI: From Fragmented Knowledge to Intelligent Systems
In the session “Enterprises, KM, & AI: From Fragmented Knowledge to Intelligent Systems,” Jess DeMay (Enterprise Knowledge) and Rachel Teague (Emory Consulting LLC.) co-presented at KMWorld 2025, exploring how organizations can evolve from disconnected information environments into intelligent and adaptive … Continue reading
Taxonomist Role in the New World of Generative AI
We have been at the forefront of implementing generative technologies to augment traditional taxonomy workflows offering new capabilities for content modeling, classification, and semantic enrichment. This raises an important question for practitioners: What are the implications of Generative AI for … Continue reading
Where AI is Failing Organizations Without a Semantic Layer: Lessons From the Trenches (with Case Studies)
It has been over three years since OpenAI, an artificial intelligence research company, introduced ChatGPT in November 2022. While artificial intelligence has existed for decades prior, this release and development of Generative AI (GenAI), large language models (LLMs), and their … Continue reading
The Cost of Missing Critical Connections in Data: Suspicious Behavior Detection using Link Analysis
Graph-powered link analysis, combined with natural language processing (NLP), offers a powerful approach to identifying complex patterns and trends within extensive and complex datasets, especially unstructured data like emails, documents, and social media. By modeling data as interconnected entities and … Continue reading
Generating Structured Outputs from Unstructured Content Using LLMs
Long, unstructured documents can be difficult to find, manage, and work with for both people and AI. A clear structure is essential for transforming and dividing disorganized content into smaller, usable, and more valuable information assets. A well-formed content structure … Continue reading
Semantic Layer Symposium 2025: Takeaways and Looking Ahead at Semantic Layers and AI
In October of this year, Enterprise Knowledge held our annual Semantic Layer Symposium (SLS) in Copenhagen, Denmark, bringing together industry thought leaders, data experts, and practitioners to explore the transformative potential, and reflect on the successful implementation, of semantic layers. … Continue reading
How to Design Taxonomies that Reflect Organizational Differences, For Humans and AI
One of the key steps to prepare your content and data for AI is developing taxonomies that identify, organize, and define the terms used in the organization in order to better structure and contextualize knowledge assets for use in AI … Continue reading
Tracing the Thread: Decoding the Decision-Making Process with GraphRAG
Does your AI tool have a hard time answering complex questions? Maybe you should consider GraphRAG! During their presentation “Tracing the Thread: Decoding the Decision-Making Process with GraphRAG” at Enterprise Search & Discovery 2025, Enterprise Knowledge’s Urmi Majumder and Kaleb … Continue reading