Vertex AI Vector Search

What Vertex AI Vector Search is

Vertex AI Vector Search is a vector search engine for search, recommendations, and generative AI applications. It uses Google Research’s ScaNN algorithm and supports dense embeddings, sparse embeddings, and hybrid search combining semantic and keyword matching. Numeric and text attribute filters can narrow searches. Google describes uses including retrieval-augmented generation, chatbots, and multimodal search. Indexes can be deployed to public or private endpoints, including Private Service Connect configurations for private access to serving backends from multiple user VPC networks. Documented integrations include RAG Engine, Cloud Storage, Cloud Run, TensorFlow Recommenders, and LlamaIndex. Python and Java clients, a Python SDK, and REST API workflows are documented. Security controls include VPC Service Controls and customer-managed encryption keys. Pricing is usage based: serving is charged per node hour, with separate index build, update, and streaming update charges. Build and update data processing costs $3.00/GiB in all regions; streaming inserts cost $0.45/GiB, while serving rates vary by machine type and region. New Google Cloud customers can receive $300 in trial credits.