Content related to How a Semantic Layer Transforms Engineering Research Industry Challenges
AI & Taxonomy: the Good and the Bad
The recent popularity of new machine learning (ML) and artificial intelligence (AI) applications has disrupted a great deal of traditional data and knowledge management understanding and tooling. At EK, we have worked with a number of clients who have questions–how … Continue reading
Extracting Knowledge from Documents: Enabling Semantic Search for Pharmaceutical Research and Development
The Challenge A major pharmaceutical research and development company faced difficulty creating regulatory reports and files based on years of drug experimentation data. Their regulatory intelligence teams and drug development chemists spent dozens of hours searching through hundreds of thousands … Continue reading
The Minimum Requirements To Consider Something a Semantic Layer
Semantic Layers are an important design framework for connecting information across an organization in preparation for Enterprise AI and Knowledge Intelligence. But with every new technology and framework, interest in utilizing the technological advance outpaces experience in effective implementation. As … Continue reading
The Resource Description Framework (RDF)
Simply defined, a knowledge graph is a network of entities, their attributes, and how they’re related to one another. While these networks can be captured and stored in a variety of formats, most implementations leverage a graph based tool or … Continue reading
Enterprise AI Architecture Series: How to Extract Knowledge from Unstructured Content (Part 2)
Our CEO, Zach Wahl, recently noted in his annual KM trends blog for 2025 that Knowledge Management (KM) and Artificial Intelligence (AI) are really two sides of the same coin, detailing this idea further in his seminal blog introducing the … Continue reading
Knowledge Cast – Ahren Lehnert at Nike
Enterprise Knowledge CEO Zach Wahl speaks with Ahren Lehnert, Principal Taxonomist at Nike. In this conversation, Zach and Ahren discuss the future of taxonomy and artificial intelligence (AI), emphasizing both the augmentation of traditional roles and growth to include new … Continue reading
Metadata Within the Semantic Layer
As a standardized framework for connecting organizational assets, a Semantic Layer captures organizational knowledge and domain meaning to support connecting and coordinating assets across systems and repositories. Metadata, as one component of a Semantic Layer approach, is foundational. Whether you … Continue reading
Enterprise AI Architecture Series: How to Build a Knowledge Intelligence Architecture (Part 1)
Since the launch of ChatGPT over two years ago, we have observed that our clients are increasingly drawn to the promise of AI. They also recognize that the large language models (LLMs), trained on public data sets, may not effectively … Continue reading
Enterprise AI Meets Access and Entitlement Challenges: A Framework for Securing Content and Data for AI
In today’s digital landscape, organizations face a critical challenge: how to leverage the power of Artificial Intelligence (AI) while ensuring their knowledge assets remain secure and accessible to the right people at the right time. As enterprise AI systems become … Continue reading
Multimodal Graph RAG (mmGraphRAG): Incorporating Vision in Search and Analytics
David Hughes, Principal Data & AI Solution Architect at Enterprise Knowledge, presented “Unleashing the Power of Multimodal GraphRAG: Integrating Image Features for Deeper Insights” at Data Day Texas 2025 in Austin, TX on Saturday, January 25th. In this presentation, David … Continue reading