Content related to LLM Solutions PoC to Production: From RAGs to Riches (Part 1)
What is the Difference Between a Semantic Layer and a Context Layer? When to Use a Knowledge Graph vs. a Context Graph
Before AI became part of everyday conversations, most enterprise knowledge and data projects had a somewhat straightforward goal: to create a “single source of truth.” In theory, this meant that everyone in the company could look at the same search … Continue reading
Leveraging a Semantic Layer for Research Curation and Conversational Experiences
The Challenge A global philanthropic organization focused on health programs struggled to fully leverage knowledge from semi-structured and unstructured documents. Specifically, within a health-related funding program, researchers lacked access to key qualitative data from end-user surveys and transcripts. Consequently, they … Continue reading
Building the Semantic Layer: Scaling Enterprise Intelligence at a Global Investment Firm
The Challenge A global investment firm with a $330 billion dollar portfolio and 50,000+ employees struggled with fragmented data. Investment professionals were losing critical time hunting for assets across disconnected systems. Detailed deal records were scattered as a mix of … Continue reading
GraphRAG in the Enterprise
Retrieval-Augmented Generation (RAG) is a commonly utilized pattern for grounding large language models in enterprise data. Instead of solely relying on a model’s training, RAG collects relevant information from internal sources, documents, knowledge bases, and other systems; it then uses … Continue reading
Knowledge Cast – TJ Hsu, Director of R&D Knowledge Management at Amgen
Enterprise Knowledge CEO Zach Wahl speaks with TJ Hsu, Director of R&D Knowledge Management at Amgen. With over a decade of experience in artificial intelligence and knowledge services, TJ currently leads a team dedicated to enhancing Amgen’s research, development, and … Continue reading
Graph-Based Security & Entitlements: Transforming Access Control for the Modern Enterprise
Introduction Modern organizations face significant challenges in managing entitlements across their increasingly complex technology landscapes. The proliferation of cloud-native architectures and Software-as-a-Service (SaaS) platforms has dramatically expanded the digital footprint of most organizations. Critical assets, including sensitive data, analytics, collaboration … Continue reading
Understanding the New Knowledge, Data, and AI Ecosystem: Trends in Enterprise AI Architecture
The way we consume, create, and engineer information has changed dramatically, with the last several years demonstrating a marked transformation due to Artificial Intelligence (AI). According to a recent report, Generative AI adoption has reached a tipping point, with nearly … Continue reading
Optimizing Historical Knowledge Retrieval: Extracting Knowledge by Making Connections
The Challenge From POC to Production A Federally Funded Research and Development Center (FFRDC) faced significant challenges with low-quality or incomplete metadata for managing and cataloging scientific reports, hindering researchers’ ability to parse repositories and efficiently discover relevant content. As … Continue reading
What Are Explainable AI Knowledge Portals and Why Do You Need Them?
Knowledge Portals first came into prominence in the early 2000s. These initial portals were a collection of static links to information on everything from HR systems to company policies and communications. It was a single location to access the systems … Continue reading
Graph Database Evaluation for a Financial Services Firm
A financial services firm built a mature graph data ecosystem, but the graph database they selected originally did not scale as multiple business-critical solutions relied on graph data. As application and business teams across multiple stakeholder groups expanded usage … Continue reading