Neo4j

Neo4j is the primary graph database. Members, personas, circles, expertise, contributions, governance state, and network relationships all live in Neo4j. Graph algorithms (community detection, centrality, pathfinding) run directly against the stored topology.

Graph Storage and Analytics

Neo4j's native graph storage handles both transactional and analytical workloads. The Graph Data Science library runs scoring, ranking, and pattern detection on the live network graph without ETL.

Graph Data Science

The Neo4j GDS library powers relationship analysis across the membership graph. These computed features feed into the CES scoring model and the Fixie AI agents' context retrieval.

Key Applications in ƒxyz Network

ƒxyz Network utilizes Neo4j for several critical functions:

Financial Network Mapping

Neo4j powers our financial cartography efforts, storing complex relationships between financial entities, assets, and transactions.

Pattern Detection and Analysis

Using Neo4j's graph algorithms, we identify patterns and anomalies in financial data that might not be apparent through traditional analysis methods.

Knowledge Graph Foundation

Neo4j serves as the foundation for our knowledge graphs, integrating various data sources to create a comprehensive view of financial information.

Integration with AI Systems

The Fixie agents query Neo4j for member context, circle state, and graph relationships when answering questions or executing tasks.

Technical Implementation

The Neo4j stack:

• Neo4j Enterprise Edition: Primary graph store
• Neo4j Graph Data Science Library: Scoring, community detection, centrality
• APOC (Awesome Procedures On Cypher): Extended Cypher procedures
• neosemantics (n10s): RDF import/export and FIBO ontology mapping