Despite the excitement about Large Language Models (LLM), these models suffer from hallucinations problems, e.g., generating factually incorrect text. These problems restrict the development of production-ready applications. This talk will highlight the importance of combining Knowledge Graphs with Large Language Models to develop industry-ready applications. We will present different approaches, from pragmatic to under-research approaches to threat and handle hallucination problems using Knowledge Graphs at different phases of the LLM lifecycle. We will accompany our presentation with use cases that Fraunhofer works with partners from big German industries under the OpenGPT-X project.