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An enterprise organization wants to implement an internal knowledge discovery platform across disparate repositories, including unstructured PDF policy manuals in Cloud Storage, structured employee directory tables in BigQuery, and public-facing corporate websites.
The development team needs an out-of-the-box solution that supports semantic search, extracts keywords automatically, and generates Large Language Model (LLM) answers grounded in internal data with citations, without having to manually generate embeddings or manage vector index sharding.
Which Google Cloud service should the cloud architect recommend?
Vertex AI Search (part of Vertex AI Agent Builder) is a fully managed platform that enables organizations to rapidly build Google-quality search engines and discovery applications across structured, unstructured, and website data repositories without requiring specialized machine learning expertise.
Vertex AI Search is the optimal choice because it provides a complete, turnkey retrieval and generative grounding solution. Unlike low-level vector engines that require developers to extract text, calculate embeddings, maintain vector databases, and implement retrieval-augmented generation (RAG) orchestration manually, Vertex AI Search delivers all of these capabilities as a managed service.
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