Vector Database Setup (Pinecone, Weaviate, Qdrant, Chroma)

We set up vector databases for teams building AI search, RAG systems, recommendation engines, and semantic features. Our team helps you pick the right platform across Pinecone, Weaviate, Qdrant, and Chroma based on scale, latency, hosting model, and budget. We then handle the full setup: index design, embedding model selection, chunking strategy, metadata schema, and access controls. We build the ingestion pipeline that keeps the database in sync with your source content, and we implement hybrid search where keyword and vector retrieval need to work together. We tune index parameters, reranking, and filters to hit your accuracy and latency targets, and we benchmark the system against your real queries. After launch we monitor index health, query performance, and cost, and we support migrations between platforms when needs change. Teams get a database that scales with their AI roadmap.