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google-cloud-solution-rag-enterprise-search-gke-sqldb

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Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.

When to use

• RAG-capable enterprise search system
• vector-enabled SQL database as store and index
• open model and open-source inferencing framework
• Kubernetes containers to host application components
• AlloyDB database, Cloud Storage, and GKE cluster
• secure, low-latency, and high-accuracy RAG-enabled conversational search
• private enterprise content search

When not to use

• fully-managed RAG
• SaaS search services
• non-SQL vector database

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