Architecture & Deployment
Vector Databases & Retrieval
Production retrieval architecture: vector DBs, hybrid search, reranking, and freshness policies. The data plane behind every RAG system we ship.
What it is
The retrieval plane is the unglamorous foundation under every well-functioning RAG system. We build production retrieval that combines vector search, lexical search, and reranking — tuned per use case, deployed inside customer infrastructure, and observable end to end.
What we deliver
- Vector database deployment (Qdrant, Weaviate, pgvector, or managed) inside customer VPC
- Embedding compute internal to the customer environment
- Hybrid retrieval: BM25 + dense + reranker pipeline
- Freshness and re-indexing strategies tuned to your update cadence
- Retrieval evaluation: hit rate, MRR, recall at K
- Per-tenant index isolation in multi-tenant deployments
Why this matters
Most RAG performance issues are retrieval issues, not generation issues. Investing in the retrieval architecture pays back across every downstream model interaction.
Industries that use this
Where it ships.
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