Read about how the idea of a semantic layer started, what are its elements, and how we can use it to enhance the performance of large language models
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Andreas Blumauer
Andreas Blumauer is the Senior Vice President of Growth at Graphwise, the company formed through the merger of Ontotext and the Semantic Web Company (SWC). As the founder of SWC and creator of the PoolParty Semantic Platform, Andreas has been a driving force in advancing semantic AI, knowledge graph technologies, and Retrieval-Augmented Generation (RAG) solutions.
With more than 20 years of experience, he has partnered with over 200 organizations worldwide to design and implement cutting-edge AI, semantic search, and knowledge graph solutions — empowering enterprises to unlock the full potential of their data through intelligent integration, modeling, and reasoning. In recent years, his focus has expanded to developing AI-powered ESG solutions that help companies and investors make more informed, sustainable decisions.
Thought Leadership post
Unlocking AI Trust: How RAG and GraphRAG are Transforming GenAI
Andreas Blumauer talks to AIThority about how organizations are overcoming data quality and security concerns by adopting RAG technologies.
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Blog Post
Graph Technologies and Graph RAG: Shaping the Future of Corporate Knowledge Management
Read about how recent studies reveal the potential of graph technologies and GraphRAG to enable organizations to manage data more effectively
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Event
How Graphwise Drives AI-Ready Data and Knowledge Management
Discover how Graphwise’s platform enhance AI by addressing LLM hallucinations, and boosting AI model accuracy through reasoning.
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Event
Empowering LLMs with a Semantic Layer
Learn how integrating semantic layers into LLMs can foster a better understanding of complex relationships among concepts.
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Blog Post
Introducing a Graph-based Semantic Layer in Enterprises
A graph-based semantic layer focuses on entities and their relationships rather than words, enabling more meaningful, personalized, and connected understanding of enterprise data.
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