Content related to The Journey of Data: From Raw Numbers to Actionable Insights with LLMs
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 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
Enterprise LLM Accelerator
Many organizations are looking for a reliable way to experiment with and understand the applications of generative AI such as ChatGPT and Copilot. These tools, built using complex ML components like LLMs and neural networks, offer a lot of promise … Continue reading
Tool Selection & Solutions Framework Development
We recognize that navigating the myriad of technology options and AI models available for enterprise-wide AI initiatives can be challenging. As a vendor-agnostic consultancy, we partner with and integrate a wide range of tools and AI solutions on the market. … Continue reading
AI Readiness Assessment, Benchmarking & Strategy
Many organizations are looking for a tailored framework to get started in their AI journey and help them prioritize potential projects based on relative effort and estimated return. EK’s Strategy approach consists of five core factors that are within the … Continue reading