A semantic layer provides a shared understanding of data across an enterprise, translating technical structures into business concepts. Beyond traditional BI, it supports governance, analytics, and AI by ensuring consistent definitions, traceable metrics, and explainable insights.
What is enterprise resource planning? A simple guide to how ERP systems work and why they matter for modern enterprises.
Discover how retrieval augmented generation (RAG) works, why it matters, and how enterprises use it to deliver trustworthy, context-aware AI outputs.
Improve governance, integration, and AI explainability by structuring enterprise knowledge with semantic modeling standards like RDF, SHACL, and OWL. Data is everywhere, but without structure,
Financial institutions are chasing AI-driven innovation but remain grounded by unclear, disconnected data. This white paper explores how TopBraid EDG helps you move beyond glossaries and governance tools to build a true semantic foundation—enabling trusted data, reusable assets, and explainable AI.
Harness the power of knowledge graphs to manage the metadata driving your AI architecture.​
By Steve Hedden The rise of generative AI, specifically large language models (LLM) like ChatGPT, have encouraged almost every enterprise to try to unlock or
In the evolving landscape of life sciences, managing and integrating vast amounts of complex data is more challenging than ever. Organizations are increasingly focused on
Enterprise AI pilots are everywhere—but many fail. Learn how data modeling, ontologies, and governance make GenAI work at scale.
Traditional keyword-based search engines fall short in delivering relevant results. Semantic search with knowledge graphs is the answer.
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