Unlocking Quality, Scale, and Cost-Efficient Retrieval With Mosaic AI Vector Search

Mosaic AI Vector Search is powering high-accuracy retrieval systems in production across a wide range of use cases—including RAG applications, entity resolution, recommendation systems, and search. Fully integrated with the Databricks Data Intelligence Platform, it eliminates pipeline maintenance by automatically syncing data from source to index. Over the past year, customers have asked for greater scale, better quality out-of-the-box, and cost-efficient performance. This session delivers on those needs—showcasing best practices for implementing high-quality retrieval systems and revealing major product advancements that improve scalability, efficiency, and relevance.

What You’ll Learn:

• How to optimize Vector Search with hybrid retrieval and reranking for better out-of-the-box results
• Best practices for managing vector indexes with minimal operational overhead
• Real-world examples of how organizations have scaled and improved their search and recommendation systems