Content related to Enterprise AI Meets Access and Entitlement Challenges: A Framework for Securing Content and Data for AI
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
What is a Knowledge Asset?
Over the course of Enterprise Knowledge’s history, we have been in the business of connecting an organization’s information and data, ensuring it is findable and discoverable, and enriching it to be more useful to both humans and AI. Though use … 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
Graph Solutions PoC to Production: Overcoming the Barriers to Success (Part I)
Part I: A Review of Why Graph PoCs Struggle to Demonstrate Success or Progress to Production This is Part 1 of a two-part series on graph database PoC success and production deployment. Introduction I began my journey with graphs … 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
Enhancing Taxonomy Management Through Knowledge Intelligence
In today’s data-driven world, managing taxonomies has become increasingly complex, requiring a balance between precision and usability. The Knowledge Intelligence (KI) framework – a strategic integration of human expertise, AI capabilities, and organizational knowledge assets – offers a transformative approach … Continue reading
Expertise Augmentation for Full Lifecycle AI/ML Operations
The current job market for these unique positions is dire, and delays in hiring can translate directly to delays in your projects. In-house skill gaps in AI technologies can be a formidable obstacle in your organization’s technical evolution, often blocking … Continue reading
AI Model Quality Assessment & Governance Framework
Many AI initiatives fail because there’s no plan for scale and maintenance. Has your organization already deployed AI/ML models and you’re looking for proven ways to maintain it? Working with some of the world’s largest and most complex organizations, EK … Continue reading