Presentation

Content related to Multimodal Graph RAG (mmGraphRAG): Incorporating Vision in Search and Analytics

Knowledge Cast – Wael Taha, Vice President of Enterprise Architecture at Brown Brothers Harriman

Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Wael Taha, VP of Enterprise Architecture at Brown Brothers Harriman. Over the past 12 years, Wael has dedicated his career to architecting D&A solutions and directing D&A professionals … Continue reading

Ontology and Knowledge Graph in the Age of AI and Agents

As organizations accelerate investments in AI, semantic data models, advanced analytics, and agentic transformation, lots of jargon gets thrown around, and this sometimes results in confusion about how data driven systems work. In the realm of semantic layers, one of … Continue reading

Knowledge Cast – Bridging Knowledge, Data, and AI by Zach Wahl, Joe Hilger, and Lulit Tesfaye

In this special episode of Knowledge Cast, Zach, Joe, and Lulit pass the mic to ⁠Senzing⁠‘s Paco Nathan, who interviews them about their new book Bridging Knowledge, Data, and AI: Harnessing the Semantic Layer Framework to Drive Intelligence. Paco guides … Continue reading

Semantic Layer Maturity Benchmark for a Global CPG Leader

One of the top global leaders in automotive manufacturing faced significant challenges in managing and accessing critical knowledge across its diverse teams. The company engaged Enterprise Knowledge (EK) to conduct a Knowledge Management (KM) Strategy and solution implementation project plan after the failure of multiple KM initiatives. The engagement’s long-term goal is to establish a shared Knowledge Management System (KMS) to streamline access to crucial information, better leverage experts’ institutional knowledge and experience, and decrease new employees’ time to proficiency. Continue reading

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

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