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Content related to LLM Solutions PoC to Production: From RAGs to Riches (Part 1)

Auto-Classification for the Enterprise: When to Use AI vs. Semantic Models

Auto-classification is a valuable process for adding context to unstructured content. Nominally speaking, some practitioners distinguish between auto-classification (placing content into pre-defined categories from a taxonomy) and auto-tagging (assigning unstructured keywords or metadata, sometimes generated without a taxonomy). In this article, I use ‘auto-classification’ in the broader sense, encompassing both approaches. Continue reading

Knowledge Cast – Paco Nathan, Principal DevRel Engineer at Senzing

Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Paco Nathan, Developer Relations (DevRel) Leader for the Entity Resolved Knowledge Graph Practice at Senzing. He is a computer scientist with over 40 years of tech industry experience … 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

Inside the Unified Entitlements Architecture

Today’s enterprises face a perfect storm in data access governance. The shift to cloud-native architectures has created a sprawling landscape of data sources, each with its own security model. For example, a typical enterprise might store customer data in Snowflake, … Continue reading

Optimizing Historical Knowledge Retrieval: Leveraging an LLM for Content Cleanup

Enterprise Knowledge (EK) recently worked with a Federally Funded Research and Development Center (FFRDC) that was having difficulty retrieving relevant content in a large volume of archival scientific papers. Researchers were burdened with excessive search times and the potential for knowledge loss … 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