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Uncovering Corporate Webs with Graph Intelligence

Traditional databases see rows and columns. We see connections. By scraping public data—filings, news, and registries—we build graph networks that reveal hidden risks, conflicts of interest, and market opportunities.

Relational vs. Graph

SQL (Relational) Query: JOIN x 5 tables

Slow with complex, deep relationships. Rigid schema.

Graph DB (Neo4j) Query: Traverse Paths

Lightning fast traversal. Native relationship storage.

The Data Pipeline

Turning unstructured public data into a knowledge graph.

1

Source Identification

2

Scraping & Ingestion

3

Entity Extraction

4

Graph Modeling

Live Network Simulation

Visualizing a sample dataset processed through the pipeline.

Relationship Composition

Scraping Efficacy