HNSW-Sharp

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Build, query, and extend the graph + search + AI platform.

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Ship domain-specific AI apps with custom UIs, endpoints, and connectors.

Model your data as typed nodes and edges with stable keys.

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Ground LLMs, embeddings, and agents in your own graph.

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Core Concepts

What HNSW is, the meaning of each parameter, and how distance functions plug in.

The hierarchical proximity graph at the heart of the algorithm — and why it scales so well.

M, EfSearch, EfConstruction, and the ACORN-γ filtering knobs — what each one trades.

The four CosineDistance variants, what their preconditions are, and how to plug in your own metric.