Dealing with fragmented or poorly structured data and slow, unreliable AI insights are common challenges that make it difficult to effectively deploy GenAI. Enterprise-grade AI requires a unified data strategy to provide the most accurate, reliable, and trustworthy results.

The way companies store and organize data is not conducive to successful AI systems because it doesn’t directly represent and communicate how the real world operates. Knowledge graphs help bridge this gap. In this webinar, we demonstrate how a graph intelligence architecture and agentic GraphRAG (retrieval-augmented generation with knowledge graphs) boost accuracy, improve explainability, and future proof AI systems to directly drive AI success. We will discuss Neo4j customers including What if Media Group, Qiagen (biomedical), and a major tech media company have seen tangible outcomes - 30x revenue gains, 4k + reduction in manual hours and risk reduction, and 10x faster BI insights respectively.

This webinar will show you how this all works from the ground up with a technical example. transform raw enterprise data into knowledge you can use, including:

• How knowledge graphs improve AI accuracy and trustworthiness
• How real-world companies achieve success with GenAI
• Practical steps for deploying GenAI effectively within your organization

Register now to secure your spot.