Content related to Semantic LLM Accelerator
How a Semantic Layer Transforms Engineering Research Industry Challenges
To drive future innovation, research organizations increasingly seek to develop advanced platforms that enhance the findability and connectivity of their knowledge, data, and content–empowering more efficient and impactful R&D efforts. However, many face challenges due to decentralized information systems, where … Continue reading
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
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
From Enterprise GenAI to Knowledge Intelligence: How to Take LLMs from Child’s Play to the Enterprise
In today’s world, it would almost be an understatement to say that every organization wants to utilize generative AI (GenAI) in some part of their business processes. However, key decision-makers are often unclear on what these technologies can do for … Continue reading
Aligning an Enterprise-Wide Information Management (IM) Roadmap for a Global Energy Company
A global energy company sought support in detailing and aligning their information management (IM) team’s roadmaps for all four of their IM products – covering all managed applications, services, projects, and capabilities – to help them reach their target state vision of higher levels of productivity, more informed decision-making, and quality information made available to … 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
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
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