Driving GenAI Success in Production: Proven Approaches for Data Quality, Context, and Logging

Alison Cossette, Developer Advocate at Neo4j, discusses how to achieve business value with Generative AI in production, focusing on Retrieval-Augmented Generation (RAG) applications. The talk covers essential aspects of data quality, the importance of non-semantic context, and the strategic role of logging. Key themes include a methodology for dataset construction for RAG excellence, navigating context with awareness of limitations in distance metrics like Cosine Similarity, and leveraging meticulous logging for application health and business insights. Takeaways include 6 requirements for GenAI data quality, adding context beyond just vectors, and the strategic significance of logging. The presentation explores how knowledge graphs can enhance RAG applications and provide valuable business insights.