Overview#
A cryptocurrency forensics team is tracing stolen funds. The theft happened three weeks ago. Since then, the funds have moved through 23 intermediate wallets, two mixing services, four exchange deposit addresses, and a cross-chain bridge before landing in addresses linked to a known criminal group. Finding that path manually would take days. The pathfinding module finds it in seconds, ranks every alternative route, and flags which intermediaries sit on known sanctions lists.
The Graph Pathfinding and Routing module delivers advanced path discovery capabilities across multi-million node graphs. Seven integrated pathfinding algorithms discover optimal routes, rank alternative paths, and enforce business constraints during navigation. This applies across fund flow tracing, criminal network connection discovery, compliance-aware transfer validation, and supply chain analysis.
Diagram
flowchart LR
SRC[Source Node] --> ALG[Pathfinding Engine]
ALG --> SP[Shortest Path]
ALG --> KSP[K-Shortest Paths]
ALG --> BD[Bidirectional Search]
ALG --> CR[Constrained Routing]
ALG --> MC[Multi-Criteria]
ALG --> TD[Time-Dependent]
SP --> RANK[Path Ranking]
KSP --> RANK
BD --> RANK
CR --> RANK
MC --> RANK
TD --> RANK
RANK --> DST[Destination Node]
RANK --> RPT[Investigation Report]Key Features#
- Seven routing algorithms including shortest path, heuristic-guided search, bidirectional search, K-shortest paths, constrained routing, multi-criteria optimisation, and time-dependent routing
- High routing success rate finding valid paths even with complex constraint configurations
- 15+ path constraint types including node exclusion, required waypoints, edge type filtering, weight thresholds, and temporal constraints
- Bidirectional search significantly reducing pathfinding time by searching from both endpoints simultaneously
- Alternative route discovery through the K-shortest paths algorithm with diversity scoring and similarity filtering
- Constraint-based routing enforcing required waypoints, forbidden zones, edge restrictions, and multi-criteria optimisation
- Multi-criteria path scoring combining weight, hop count, risk, trust, diversity, and custom metrics
- Time-dependent routing handling graphs where edge weights vary over time for realistic temporal modelling
- Pareto-optimal solution discovery for balanced multi-objective decision making
- Path ranking with configurable scoring models and explainable results
- Automatic algorithm selection based on graph properties and query characteristics
- Custom heuristic functions for domain-specific acceleration of path search
Use Cases#
- Fund Flow Tracing: Cryptocurrency forensics teams trace fund movements through complex transaction networks, identifying paths through mixing services and exchanges
- Criminal Network Connection Discovery: Law enforcement investigators find connections between suspects through relationship graphs with configurable relationship type constraints
- Logistics Route Optimisation: Companies optimise delivery routes with time-dependent routing that accounts for traffic patterns and temporal constraints
- Compliance-Aware Routing: Financial institutions find compliant transfer paths that satisfy regulatory constraints including sanctioned entity avoidance and required intermediary verification
Integration#
- Connects with the Neo4j graph analysis layer for path computation across investigation and operational data
- Compatible with investigation platforms for automated target prioritisation based on path analysis
- Supports real-time path queries through typed APIs with configurable timeouts
- Node-level access controls ensure traversals respect security permissions
- Multi-tenant graph isolation prevents cross-tenant path discovery
- Automatic redaction of sensitive node properties in path results
- Compliance with GDPR, SOC 2, ISO 27001, and CCPA data protection standards
Last Reviewed: 2026-02-05 Last Updated: 2026-04-14