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Explainable Enterprise AI with Neo4j and Mistral AI

What if your AI could actually understand how your business connects? Most AI systems generate answers. Few can reason across the relationships, dependencies, and context that make enterprise data meaningful. That gap becomes critical when data is complex, interconnected, and high-stakes — and when wrong answers carry real consequences. Join Neo4j for a live demonstration of graph-powered GenAI and discover how organizations are grounding AI in trusted enterprise knowledge to improve accuracy, governance, and business outcomes. The difference is context. GraphRAG grounds AI reasoning in connected enterprise data. That means more accurate answers, clearer traceability, and a more intuitive way to navigate complex systems — whether your data is structured, unstructured, or both. You’ll see how Neo4j and Mistral AI work together through MCP-based agentic workflows to build AI that doesn’t just answer questions — it understands why those answers matter.
What you’ll learn
  • Why connected data improves AI reasoning and reduces hallucinations
  • How GraphRAG delivers explainability and traceability in practice
  • How agentic workflows using MCP and Cypher unlock complex data navigation
  • Why data sovereignty matters for enterprise AI — and how to achieve it
  • How to connect structured and unstructured data in a single AI architecture
Why Neo4j and Mistral AI? Enterprise AI needs more than a powerful model. It needs context — and control. Neo4j helps AI understand how data connects across assets, systems, operations, and decisions. Mistral AI adds a fast, flexible conversational layer: a European model designed for enterprise deployment, without dependence on proprietary US cloud infrastructure. Together they deliver AI that is:
  • More context-aware
  • Easier to trust and explain
  • Deployable on your terms, in your environment
  • Designed for complex, connected data — structured or unstructured
AI works differently when it understands how your data connects. Join us to see what that looks like.
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