Enterprise-grade agentic AI applications require vector databases that can scale to billions of vectors, a challenge current systems often fail to meet. AlloyDB, a PostgreSQL-compatible database service, is engineered for these demanding workloads, offering high availability and scalability with its integrated analytical engine. A key advancement is its ScaNN index, now efficiently handling 10 billion vectors through a new four-level tree architecture. This innovative design significantly reduces computation intensity by employing hierarchical partitioning, drastically narrowing the search space during queries. The four-level structure achieves optimal traversal efficiency with a complexity of O(N1/4), surpassing previous limitations. Furthermore, the architecture enhances memory usage through balanced tree construction and optimized sampling processes. These strategies allow AlloyDB ScaNN to manage large datasets without exceeding available memory capacity. Performance tests demonstrate that AlloyDB can effectively scale to over 10 billion vectors using its ScaNN index. It achieves under 51ms p95 latency and 95% recall at this massive scale. Users can now experience this four-level tree architecture through a quickstart guide and a 30-day free trial.