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CORE_CAPABILITY

Link Analysis & Relationship Mapping

Turn scattered records into a graph of people, organizations, accounts, and events — revealing networks that stay hidden in tables.

Neo4jGraph AlgorithmsD3.jsPostgreSQLTypeScript

The most important connections rarely appear in any single table. They hide between sources — company registries, transaction lists, contact records. Reading rows one at a time can never reveal the shape of a network.

We build systems that convert this data into a graph: people, organizations, accounts, and events become nodes; relationships become edges. Users can find paths between two seemingly unrelated entities, identify key intermediaries, and trace every edge back to its source.

  • Automatically build relationship graphs from multiple data sources
  • Find connecting paths between people or organizations
  • Analyze network centrality and community clusters
  • Correlate events across time
  • Reference source documents for every relationship

FEATURE_MATRIX

Key Features

Interactive graph exploration

Expand, filter, and drill into relationship networks directly — no query language required.

Path finding between entities

Answer “how are these two connected?” in seconds, even in large graphs.

Network analytics

Centrality and community algorithms highlight the nodes worth investigating first.

Traceable provenance

Every edge links back to its source records, keeping the analysis defensible.