CEREBRAL bloghttps://crbrl.ai/blog/AI search infrastructure, vector + graph retrieval.en-auVector database storage costs: when your vectors get smaller, does your bill?https://crbrl.ai/blog/vector-database-storage-costs/https://crbrl.ai/blog/vector-database-storage-costs/Sat, 24 Oct 2026 09:00:00 +1100Compression is the headline in vector search. Where vector storage cost really sits, what compression can mean, and three questions to ask any provider about who keeps the savings.GraphRAG's hidden cost isn't the graph. It's the sync job.https://crbrl.ai/blog/graphrag-hidden-cost-sync-job/https://crbrl.ai/blog/graphrag-hidden-cost-sync-job/Sat, 24 Oct 2026 09:00:00 +1100Running a graph database beside a vector database means two writes and no shared transaction. What that costs in production GraphRAG, when a separate graph still makes sense, and a checklist before you scale.Hybrid search for RAG: start with what the question needshttps://crbrl.ai/blog/hybrid-search-for-rag/https://crbrl.ai/blog/hybrid-search-for-rag/Sat, 24 Oct 2026 09:00:00 +1100Exact match, meaning or relationships? A practical way to route RAG retrieval between keyword, vector and graph search, with examples you can test on your own data.Your embeddings are your data: five questions for sovereign AI searchhttps://crbrl.ai/blog/sovereign-ai-search-embeddings-are-your-data/https://crbrl.ai/blog/sovereign-ai-search-embeddings-are-your-data/Sat, 24 Oct 2026 09:00:00 +1100Embeddings, indexes and relationship data are built from your contracts, tickets and policies. Five questions for risk, data and platform leads about where AI search data really lives.