Blog Archives

Knowledge Cast – Michal Bachman, CEO of GraphAware

Enterprise Knowledge COO Joe Hilger speaks with Michal Bachman, CEO at GraphAware. GraphAware provides technology and expertise for mission-critical graph analytics, and its graph-powered intelligence analysis platform — Hume — is used by democratic government agencies (law enforcement, intelligence, cybersecurity, … Continue reading

Webinar: Semantic Graphs in Action – Bridging LPG and RDF Frameworks

As organizations increasingly prioritize linked data capabilities to connect information across the enterprise, selecting the right graph framework to leverage has become more important than ever. In this webinar, graph technology experts from Enterprise Knowledge Elliott Risch, James Egan, David … Continue reading

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

Semantic Graphs in Action: Bridging LPG and RDF Frameworks

Enterprise Knowledge is pleased to introduce a new webinar titled, Semantic Graphs in Action: Bridging LPG and RDF Frameworks. This webinar will bring together four EK experts on graph technologies to explore the differences, complementary aspects, and best practices of … 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

Semantic Layer Strategy for Linked Data Investigations

A government organization sought to more effectively exploit their breadth of data generated by investigation activity of criminal networks for comprehensive case building and threat trend analysis. EK engaged with the client to develop a strategy and product vision for their semantic solution, paired with foundational semantic data models for meaningful data categorization and linking, architecture designs and tool recommendations for integrating and leveraging graph data, and entitlements designs for adhering to complex security standards. Continue reading