OverviewNexus Network Mapping

Nexus Network Mapping

See the connections others miss

How It Works

Step through the process to see how it works.

1

Entity Selection

Start with a person of interest. The system loads the entity and prepares to explore their relationship network.

Nexus Network Analysis

Ahmed K.Tariq M.Saeed R.Org-XFarhan H.Imran S.Rashid P.Cell-7Nawaz A.Waqar L.
Step 1 of 6

Key Features

Core capabilities that power this module.

Neo4j Graph Engine

Persistent graph database handles millions of relationships with sub-second traversal queries.

Community Detection

Louvain and label propagation algorithms identify operational cells and organizational structures.

Centrality Metrics

Betweenness, degree, and eigenvector centrality scores identify key brokers and influencers.

Path Finding

Shortest path algorithms discover hidden connections between seemingly unrelated entities.

Scenario: Investigating Ahmed Khalil

A realistic walkthrough using fictional intelligence data.

An analyst begins investigating Ahmed Khalil after a new intelligence report flags him in connection with a border crossing incident. Using Nexus, the analyst expands his network to discover hidden relationships.

1First-degree expansion reveals 5 direct contacts — 3 persons, 1 organization (Org-X), 1 shared location
2Second-degree expansion adds 14 more entities, revealing Tariq Masood as a shared connection to Cell-7
3Community detection identifies 3 distinct clusters — Ahmed's immediate circle, an Org-X operational cell, and a financial network
4Centrality analysis reveals Tariq Masood has the highest betweenness score — he's the hidden broker connecting two groups
5Shortest path between Ahmed Khalil and a previously unrelated suspect goes through Tariq (3 hops)
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