Max Gärber: Agentic AI Built on a Knowledge Graph Foundation – Episode 45 скачать в хорошем качестве

Max Gärber: Agentic AI Built on a Knowledge Graph Foundation – Episode 45

Max Gärber The promise of agentic AI is being realized in systems like the Service Copilot that Zeiss microscopes provides for its field service engineers. The system integrates technical documentation, subject matter expertise, and user-generated insights which are orchestrated and shared with a suite of AI agents. While it relies heavily on modern LLM technology, it's the system's solid knowledge graph and metadata foundation that make it a success. We talked about: Max's work "turning information into value" at PANTOPIX, a technical documentation and information processes consultancy based in Germany a recent client project working with Zeiss to help their field service engineers operate more efficiently how their prior knowledge management and machine learning work helped them not only cope, but thrive, at the arrival of ChatGPT and LLMs the immediate positive stakeholder feedback they received as they incorporated LLMs into their knowledge architecture how they extended the iiRDS standard with a custom ontology and taxonomies and integrated topic mappings into their system and workflows an overview of the system architecture and tooling, which includes both a graph database and a vector store, an ontology and taxonomy management tool, and documentation of best practices their evolution from simple prompt engineering and RAG approach to an agentic orchestration architecture a few of the agents in their architecture: a planning agent that organizes and orchestrates a content agent that replaces the original RAG system a troubleshooting agent which surfaces past solutions the good problem they experienced of managing enthusiastic user adoption of the new system the unexpected benefits to the Zeiss sales team of the system how subject matter expertise, user generated content, and other insights are captured and used the crucial role of knowledge management practices, structured content, and semantic technology in building the foundation for an organization's AI capabilities Max's bio Maximilian Gärber is Partner and Principal Technical Consultant at PANTOPIX. Max has been working in the field of technical communication for over 15 years. As a Partner and Technical Consultant at PANTOPIX, he is responsible for the technical consultation and implementation of projects. In addition to project management, Max is responsible for data modelling and process optimization in relation to product information (migration, publication, translation) and product catalogues. He is also responsible for product development and ensures that innovative solutions for our customers are continuously developed and optimized. Connect with Max online LinkedIn PANTOPIX Resources mentioned in this episode Industrial Knowledge Graph meets Agentic AI: Service Copilot at ZEISS RMS slide deck Service Copilot from ZEISS article Video Here’s the video version of our conversation: https://www.youtube.com/embed/ttQOHvv... Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 45. When you're a field service engineer dealing with both the typical challenges of information overload and the need to maintain complex machinery like a high-end Zeiss microscope, you'd really benefit from an intelligent knowledge management system, one that integrates technical documentation, subject matter expertise, and user-generated insights. That's exactly what Max Gärber has built - an agentic AI system grounded in a solid knowledge graph foundation. Interview transcript Larry: Hi everyone. Welcome to episode number 45 of the Knowledge Graph Insights podcast. I am really excited today to welcome to the show Max Garber. Max did a really interesting presentation at the Semantics conference in Vienna last fall, and I've been trying to get him on the show ever since. So here he is. I'm excited to have him here. Max, he's a partner and a technical consultant at PANTOPIX, a consultancy based here in Germany. Welcome, Max. Tell the folks a little bit more about what you're doing these days. Max: Yeah, thanks Larry. Thanks for having me. Yeah, great show. And yeah, we are mostly concerned with helping mainly our industrial customers structure their content and integrate it from various sources into their systems, delivery systems, wherever it is needed. So yeah, it's mainly consultancy on data modeling, on how to do information processes and how to get the best out of your data, so to say. So our mission here is literally turning information into value. Larry: Oh, I love that. That's a great tagline for a consultancy. Well, you did the use case, the case study you talked about in Vienna was really interesting to me. This issue of Zeiss microscopes, in particular their research microscopy solutions arm, which is these big, expensive, complex machines that require a lot of service. Can you talk a little bit about how you got involved with Zeiss and what you do to help them? In part...