Speaker: Courtlin Holt-Nguyen – Head of Data and AI, QIMA
Description
A technical exploration of graph-enhanced RAG architectures that support natural language querying of complex technical knowledge bases. The session examines how combining knowledge graphs with RAG systems creates powerful capabilities for answering user questions that require an understanding of the intricate relationships between technical standards, standard operating procedures, and regulatory requirements. We’ll dive deep into the architectural principles, implementation considerations, and technical strategies that enable these systems to handle the sophisticated needs of technical operations in regulated environments at enterprise scale.
Key Takeaways:
1. Architectural insights into building graph-enhanced RAG systems that can accommodate complex technical documentation
2. Implementation strategies for combining knowledge graphs with RAG systems to capture and utilize relationships between technical standards, standard operating procedures, and compliance requirements
3. Practical approaches to measuring ROI and managing risks when deploying advanced RAG systems
