RAG is fundamental to real-world agents, but accuracy limitations persist. This talk presents Google Cloud's research on improving RAG for practical applications. We'll discuss findings from real-world deployments and share our approaches to intelligent knowledge integration, end-to-end tuning, and other techniques achieving state-of-the-art performance, demonstrating how we're making RAG more reliable for real-world scenarios.