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    Artificial Intelligence

    Vector Database Engineering

    Scalable storage + query infrastructure for embedding vectors.

    RAG systems, semantic search, recommendation engines — all rest on a vector database. The wrong choice forces re-architecture later. We weigh data volume, query latency, KVKK compliance and existing-stack fit together to pick correctly between pgvector / Qdrant / Weaviate.

    Tools and technologies we work with

    pgvectorQdrantPineconeWeaviateMilvus

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    Let's evaluate your project's scope in a free preliminary call. The 30-60 minute call delivers a budget range and a proposed approach.

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