Content related to Enterprise AI Architecture Series: How to Extract Knowledge from Unstructured Content (Part 2)
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
Data Governance for Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) has emerged as a powerful approach for injecting organizational knowledge into enterprise AI systems. By combining the capabilities of large language models (LLMs) with access to relevant, up-to-date organizational information, RAG enables AI solutions to deliver context-aware, accurate, … Continue reading
Beyond Content Management for Real Knowledge Sharing
Enterprise Knowledge’s Urmi Majumder and Maryam Nozari presented “AI-Based Access Management: Ensuring Real-time Data and Knowledge Control” on November 21 at KMWorld in Washington, D.C. In this presentation, Urmi and Maryam explored the crucial role of AI in enhancing data … Continue reading
Modern Methods for Managing Data Security
Enterprise Knowledge’s Joe Hilger, COO, and Ian Thompson, Technical Solutions Consultant, presented “Modern Methods for Managing Data Security” at CDOIQ in Boston, MA on Wednesday, July 17, 2024. In this presentation, Joe and Ian explored the evolving challenges of securing … 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
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