Google's Vertex AI platform has integrated generative AI capabilities, including the PaLM 2 chat model and an in-console generative AI studio, to democratize access to generative AI. This integration is backed by robust security, data governance, and scalability. Foundation models like PaLM 2 are crucial for generating human-like text, but they have limitations such as requiring domain-specific data and computational resources. A high-performance data layer, often a vector database like Redis, is essential to balance these limitations. GCP's unified offering marries powerful foundation models with scalable infrastructure and tools for tuning and deploying these models. Redis steps in as a complementary high-performing and scalable data layer, facilitating caching, semantic search, and efficient AI agent task execution. The combination of GCP and Redis provides a reliable and time-tested foundation for LLM applications, empowering them to deliver factual, accurate, and valuable interactions.