Graphlytic

Step 1: Ingest transactional data into a graph database.

Step 2: Visualize connections between accounts, transactions, and individuals.

Step 3: Apply filters to highlight suspicious patterns.

Step 4: Investigate flagged connections to identify fraudulent activity.

Step 1: Import IT asset data into a graph database.

Step 2: Visualize network topology and dependencies.

Step 3: Identify critical paths and potential points of failure.

Step 4: Monitor asset health and performance in real-time.

Step 1: Collect communication data from email, messaging, and social platforms.

Step 2: Represent communication relationships in a graph database.

Step 3: Visualize communication networks within teams and departments.

Step 4: Analyze communication patterns to identify key influencers and communication bottlenecks.

Step 1: Parse code into a graph database representing dependencies.

Step 2: Visualize code structure and dependencies.

Step 3: Identify duplicated code and potential refactoring opportunities.

Step 4: Generate code documentation based on the graph model.

Step 1: Import entity and ownership data into a graph database.

Step 2: Visualize ownership structures and relationships.

Step 3: Apply algorithms to identify UBOs based on direct and indirect ownership.

Step 4: Generate ownership reports for compliance purposes.