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Generative AI Powered by Knowledge Graphs

Unleashing the potential of Semantic Retrieval Augmented Generation

Enterprise Knowledge Graphs – Transforming Data into Knowledge


Andreas Blumauer, CEO & Co-founder, Semantic Web Company


May 23, 2024



San Francisco | 7:00 a.m. – 8:00 a.m. PDT
New York | 10:00 a.m. – 11:00 a.m. EDT
Vienna | 4:00 p.m. – 5:00 p.m. CEST

What is Retrieval Augmented Generation (RAG)?

There has been a lot of buzz about the capabilities of Large Language Models (LLMs). We have witnessed instances where the outcomes produced by LLMs are impressive, or at the very least, sound impressive, while at other times, the results may fall short. However, relying solely on an open-source LLM poses a few challenges – the information provided may be inaccurate, outdated, and lack clear sourcing. Retrieval Augemented Generation, or RAG, is a framework designed to enhance LLMs’ accuracy, relevance, and traceability by supplementing user-generated prompts with primary source data.

Leveraging Semantic Technology to enhance the capabilities of RAG

As we have seen, the possibilities for hallucinations (creation of false or misleading information)  in LLMs is high. When looking at Generative AI in content creation, this defeats the purpose to assist the knowledge user in content creation by providing quick and reliable information. Worse yet, this poses a serious risk of disseminating inaccurate information in critical sectors such as pharmaceuticals, insurance, and health & safety, where even a single piece of incorrect data can have disastrous consequences. 

Unlocking the true potential of Generative AI hinges on building AI you can rely on, or “AI you trust”. This ushers the need for combining LLMs with a myriad of tools and AI methodologies to develop trustworthy Generative AI solutions. Enter Semantic Retrieval Augmented Generation or Semantic RAG – a specialized technique in Advanced Retrieval Augmented Generation that leverages Semantic technology to seamlessly fuse knowledge models and retrieved data during the content generation process.

Join our webinar to dive into details of Semantic RAG, such as:

  • Overcoming the limits of LLMs
  • Combining LLMs with other tools to create “AI you trust.”
  • Building Generative AI on a strong Semantic base
  • Developing a Domain Knowledge Model
  • Semantic Search and Vector Search in Generative AI

Following this 30-minute webinar we will have an interactive question and answer period in which you can ask Andreas Blumauer any questions you may have about Retrieval Augmented Generation (RAG), Semantic RAG, and Generative AI.

We hope to see you there!


Andreas Blumauer

Andreas Blumauer

CEO & Co-founder, Semantic Web Company at Semantic Web Company

Andreas Blumauer is CEO and co-founder of Semantic Web Company (SWC), the provider and developer of the PoolParty Semantic Platform. With headquarters in Vienna, Austria, but operating globally, SWC has worked with over 200 commercial, government, and non-profit organizations to deliver AI and semantic search solutions, knowledge platforms, content hubs, and related data modeling and integration services. SWC was named to KMWorld’s prestigious list of “100 Companies that Matter in Knowledge Management” from 2016 to 2021 and has been named multiple times in Gartner’s Magic Quadrant for Metadata Management Solutions and as a Sample Vendor in their Hype Cycle for Natural Language Technologies.

In his role as CEO, Andreas is responsible for both the strategic growth of the company and its organizational evolution toward a highly focused customer orientation. SWC has grown every year since its inception under his leadership, and has been able to develop a cutting-edge and unique software platform that is ISO 27001 certified, and deployed globally across a number of key industries.

A high profile partner network has been built around this platform, implementing scalable semantic AI platforms for his clients, many of whom are among the largest and most innovative companies in their industries.

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