Content related to Best Practices for Enterprise Knowledge Graph Design
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
Data Management and Architecture Trends for 2025
Today, many organizational leaders are focused on AI readiness, and as the AI transformation is accelerating, so are the trends that define how businesses look for, store, secure, and leverage data and content. The future of enterprise data management and … Continue reading
A Guide to Selecting the Right Auto-Tagging Approach
Auto-tagging processes automate the manual labor of applying relevant keyword tags to data and content, enhancing accessibility and improving the organization of large datasets. Whether you’re trying to improve how quickly you find data or embarking on a content cleanup … Continue reading
Why Graph Implementations Fail (Early Signs & Successes)
Organizations continue to invest heavily in efforts to unify institutional knowledge and data from multiple sources. This typically involves copying data between systems or consolidating it into a new physical location such as data lakes, warehouses, and data marts. With … Continue reading