Anti-fraud
Investigate evolving fraud schemes and gain actionable insights with a visualization-first approach.
Dive into how fraud analysts empower digital investigations through iterative and customizable workflows.
Connection-driven intelligence
Intelligence-based workflow
Turn structured and unstructured data into a connected system AI can reason over. Kineviz combines intuitive workflows with high-dimensional graph visualization, allowing analysts to explore relationships instead of isolated records. AI-generated structure helps surface what matters, while interactive filtering removes noise—accelerating iteration and making insights traceable, explainable, and ready for decisions.
Connection-driven data model
Analysts work within a connection-driven data model built for reasoning across relationships. This graph schema doesn’t just enable traversal—it gives AI and humans a shared structure for investigation. Entities, links, and inferred connections become part of a navigable system, making it faster to uncover hidden patterns, validate findings, and move from signals to evidence-backed conclusions.
Visualisation-first approach
GraphXR accelerates fraud detection with a visualization-first reasoning environment. Seamless integration—combined with no-code Cypher querying—lets analysts see how AI-derived insights connect across the graph. Instead of black-box outputs, users explore relationships visually, trace them to source data, and refine hypotheses in real time for faster, more trustworthy fraud prevention.
Exposing Collusion in the Gaming Industry
Detecting and responding to collusion is a difficult and time-consuming process. A horse racing organization's trust and integrity team uses GraphXR to intuitively address these challenges, accelerating investigations for sports betting integrity.
