Tutorials
Learn the essentials of working with graph-connected data.
Knowledge Mapping Insurance Fraud with SightXR
Visualize webs of connections of the serial fraudster Bill Mize, walking through our new GenAI tool, SightXR. Explore the synergy between AI’s text evaluation and Q&A capability with the graph visual representation of the knowledge itself.
Traverse Networks with Quick Layouts & Find Path
With Kineviz and Neo4j, we’ll rapidly display a networked graph as a tree hierarchy, then trace and isolate subgraphs and shortest paths between nodes.
SeekerXR: How are two people connected?
Investigate the business relationships and linkages between two people using SeekerXR to pull connected information from company filings, LinkedIn and other sources.
Investigating Collusion with Search & Expand
We can begin an investigation in Kineviz & Neo4j, starting with a specific person and expanding outwards to reveal their entire network.
Investigate crime through effective visualization
Leverage Neo4j’s pre-built sandbox dataset to investigate the POLE model, from which you can expand and analyze at scale with Kineviz visualization.
From CSV to Neo4j with Kineviz
Import data from a CSV and set up a Neo4j instance to build your graph and enhance it with new properties, all visualized in Kineviz for analysis.
Frequently Asked Questions
Where can I find Kineviz (formerly GraphXR) tutorials?
Kineviz's tutorials page offers video walkthroughs for learning the essentials of working with graph-connected data. Topics include importing from CSV to Neo4j, traversing networks with quick layouts and find path, investigating collusion with search and expand, mapping insurance fraud with SightXR (a GenAI knowledge-mapping tool whose capabilities now live in Kineviz), and using SeekerXR to reveal how two people are connected.
How do I import data from CSV to Neo4j and visualize it?
Kineviz's "From CSV to Neo4j with Kineviz" tutorial walks you through importing data from a CSV, setting up a Neo4j instance, building your graph, enhancing it with new properties, and visualizing it in Kineviz for analysis. It's a practical starting point for turning tabular data into an interactive, explorable graph.
How do I find the shortest path between nodes in a graph?
Kineviz's "Traverse Networks with Quick Layouts & Find Path" tutorial shows how, using Kineviz and Neo4j, you can rapidly display a networked graph as a tree hierarchy, then trace and isolate subgraphs and shortest paths between nodes. It demonstrates layout and path-finding tools for navigating complex connected data.
How can I find out how two people are connected using graph analysis?
Kineviz's SeekerXR tutorial demonstrates investigating the business relationships and linkages between two people by pulling connected information from company filings, LinkedIn, and other sources. This entity-linking approach reveals hidden relationships, a core investigative use case for graph visualization when uncovering how individuals or organizations relate.
How do I investigate a network or crime using graph visualization?
Kineviz tutorials cover investigative workflows step by step. "Investigating Collusion with Search & Expand" starts from a specific person and expands outward to reveal their entire network in Kineviz and Neo4j, while "Investigate crime through effective visualization" uses Neo4j's pre-built POLE-model sandbox dataset to expand and analyze at scale.
What is SightXR and how does it map insurance fraud?
SightXR was Kineviz's GenAI tool for knowledge mapping; the product has since been discontinued and its capabilities folded into Kineviz. In the "Knowledge Mapping Insurance Fraud with SightXR" tutorial, it visualizes the web of connections around serial fraudster Bill Mize, showing the synergy between AI's text evaluation and Q&A capabilities and the graph's visual representation of the knowledge itself.
Can I follow along with GraphXR and Neo4j sandbox datasets?
Yes. Several Kineviz tutorials use Neo4j alongside Kineviz visualization, including one that leverages Neo4j's pre-built POLE-model sandbox dataset so you can expand and analyze at scale. Others walk through connecting Kineviz with Neo4j to trace subgraphs, find paths, and expand investigations from a single starting node.