Kineviz

GraphXR, now Kineviz, is a browser-based graph visualization and analytics platform for exploring connected data. It powers insight through intuitive visual analytics and AI-assisted discovery: you can pull data from graph or relational databases, CSV or JSON files, and third-party APIs, then visualize, analyze, and collaborate on it in an immersive browser environment — no installation required.

Kineviz (formerly GraphXR) connects directly to Neo4j and other graph databases, letting you query, visualize, and explore your graph in the browser. Beyond graph visualization, it adds graph analytics like path finding, centrality, and community detection, plus geospatial, time series, and social network views. You can fine-tune graphs on the fly with icons, portrait images, custom colors, and layouts.

OSINT investigators use graph visualization platforms to map relationships between people, accounts, and events from open sources. Kineviz (formerly GraphXR) is built for exactly this: OSINT investigations are a primary use case, alongside legal e-discovery, anti-money laundering, and collusion detection. Its AI assistance extracts entities and relationships from CSVs and many other file formats, turning raw collected data into an explorable network. For the collection step itself, Kineviz offers SeekerXR, which pulls from more than 80 OSINT and proprietary data sources.

You can visualize a knowledge graph by connecting a tool like Kineviz (formerly GraphXR) to your graph database or loading files directly. Kineviz connects to graph and relational databases, ingests CSV, JSON, and third-party API data, and fuses sources into one view. From there you explore interactively — iterating layouts, colors, and filters — and apply analytics such as path finding, centrality, and community detection.

Community detection groups densely connected nodes to reveal clusters, while centrality measures identify the most influential nodes in a network. Kineviz (formerly GraphXR) includes built-in algorithms for community detection, centrality, and shortest path. Analysts combine them with geospatial, time series, and social network views to discover hidden connections in investigations like anti-money laundering, OSINT, and collusion cases.

Yes. Kineviz (formerly GraphXR) enterprise deployments run entirely inside your own IT ecosystem — on-premises, in a private cloud, or even fully air-gapped. The platform also supports secure collaboration, providing controlled access to shared projects and charts for team members and stakeholders, which matters for law enforcement, AML, and legal e-discovery teams handling sensitive data.

Kineviz (formerly GraphXR) gives you several routes from CSV to graph: hand the file to Kineviz Agent and let it build the graph, map fields to nodes and edges yourself in Graph Composer, or shape the graph step by step with visual transforms (extract, shortcut, link, merge). The platform fuses and transforms data from a wide range of sources, including CSV and JSON files, relational and graph databases, and third-party APIs, so you can merge everything into one focused, explorable visualization.

Neo4j Bloom displays the contents of a Neo4j database. Kineviz (formerly GraphXR) treats visualization as the starting point: you can analyze, transform, fuse, model, and author graphs, and do it across many data stores rather than a single database — Neo4j and other graph databases, relational databases, CSV/JSON files, and third-party APIs. Kineviz adds AI-assisted entity extraction, built-in analytics (community detection, centrality, shortest path), geospatial and time series views, and enterprise deployment options including on-premises and air-gapped environments.