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Semantic Search Advisory and Implementation for an Online Healthcare Information Provider

The medical field is an extremely complex space, with thousands of concepts that are referred to by vastly different terms. These terms can vary across regions, languages, areas of practice, and even from clinician to clinician. Additionally, patients often communicate … Continue reading

Content Management Strategy for a Capital Producer

A capital producer understood the complexity of navigating international regulatory environments. Operating across nations in numerous fields of specialization, the organization had to uphold diverse and disparate ordinances, many of which have changed over time. Dedicated to providing high-quality services to their customers, the organization sought a solution that would help them better navigate revisions to compliance requirements and ensure adherence to rigorous standards of excellence. Continue reading

Optimizing Historical Knowledge Retrieval: Leveraging an LLM for Content Cleanup

Enterprise Knowledge (EK) recently worked with a Federally Funded Research and Development Center (FFRDC) that was having difficulty retrieving relevant content in a large volume of archival scientific papers. Researchers were burdened with excessive search times and the potential for knowledge loss … Continue reading

Content Mastermind (Taylor’s Version): What Taylor Swift Can Teach Us About The Benefits of Repurposing Content

In January of 2025, Taylor Swift charted #1 on Billboard, breaking a record for most Number 1s on the Top Album Sales list with a new version of an almost six-year-old album. The 2025 repressing of Lover (Live from Paris) … Continue reading

Graph Analytics in the Semantic Layer: Architectural Framework for Knowledge Intelligence

Introduction As enterprises accelerate AI adoption, the semantic layer has become essential for unifying siloed data and delivering actionable, contextualized insights. Graph analytics plays a pivotal role within this architecture, serving as the analytical engine that reveals patterns and relationships … Continue reading

Beyond Traditional Machine Learning: Unlocking the Power of Graph Machine Learning

Traditional machine learning (ML) workflows have proven effective in a wide variety of use cases, from image classification to fraud detection. However, traditional ML leaves relationships between data points to be inferred by the model, which can limit its ability … Continue reading

The Role of Taxonomy in Labeled Property Graphs (LPGs) & Graph Analytics

Taxonomies play a critical role in deriving meaningful insights from data by providing structured classifications that help organize complex information. While their use is well-established in frameworks like the Resource Description Framework (RDF), their integration with Labeled Property Graphs (LPGs) … Continue reading

Enhancing Insurance Fraud Detection through Graph-Based Link Analysis

A national agency overseeing insurance claims engaged EK to advise on developing and implementing graph-based analytics to support fraud detection. EK applied key concepts such as knowledge graphs, graph-based link analysis for detecting potentially suspicious behavior, and the underlying technology architecture required to instantiate a fully functional solution at the agency to address client challenges. Continue reading

How to Implement a Semantic Layer: A Proven Operating Model

As organizations invest in enterprise AI and knowledge intelligence, the semantic layer serves as a critical foundation for providing a consistent, contextual framework that connects data assets across multiple sources to enable shared understanding, interoperability, and more intelligent use of … Continue reading