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VectorSearchOps.com captures the operational side of vector search - the indexing, scaling, and management of the embeddings that power retrieval-augmented generation and modern AI search. As RAG becomes the default way to ground large language models in real data, running vector search reliably in production is a distinct and growing discipline.
The vector database market is growing fast - MarketsandMarkets projects an expansion from about USD 2.65 billion in 2025 to roughly USD 8.9 billion by 2030 - while the retrieval-augmented generation market is forecast by Grand View Research to reach around USD 11 billion by 2030. Leading vector-database vendors such as Pinecone have reached valuations of about USD 750 million.
Vector-database and AI-infrastructure vendors, RAG and enterprise-search platforms, MLOps and AI-platform teams, embedding and retrieval startups, and companies operationalizing AI search on proprietary data.
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