News


Together with BigQuery AI Functions and BigQuery Graph, GraphXR gives enterprises a streamlined way to turn unstructured data — PDFs, emails, regulatory filings — into explorable, visual knowledge graphs without complex ETL pipelines or separate graph databases.

Analysts can visually verify relationships, trace insights back to source documents, and answer complex questions interactively, all within a single workflow.

Read the full blog post by our CEO Weidong Yang and Google's Candice Chen to see how it works


Previously

A look back at some of the things we've explored.

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Graph Chat with Sony Green on the Evolution of Graph Intelligence

In this Graph Chat from ODSC, Sony Green (COO of Kineviz) joins Bryce Merkl Sasaki to discuss how graph technology is moving from a niche tool to a mainstream enterprise powerhouse. Highlights:

  • The Spanner Graph Impact: Why Google’s entry into the graph space is a watershed moment for big data and high consistency.

  • Human-Centric AI: A look at Knowledge Mapping—helping law enforcement and investigators find absolute truths in unstructured data without relying on AI-generated conclusions.

  • No-Code Graphing: Introduction of the Graph Composer, a tool designed to map disparate data sources into a graph model with zero coding.

Watch here

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Scaling unstructured enterprise knowledge with BigQuery Graph and Kineviz GraphXR

Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to access and reason over at scale. Together, BigQuery Graph and Kineviz GraphXR give decision makers power over their unstructured data by creating a single, streamlined workflow that makes it much easier to uncover hidden business insights.

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From Spanner Graph to Operational Insight: Visual Telco Analysis with Kineviz GraphXR

Communication Service Providers (CSPs) are building autonomous networks while tackling the exploding complexity of modern telecommunications. This shift requires more than just automation alone: it demands a responsive human oversight layer paired with a dynamic visualization system that can detect emerging incident patterns, retrieve relevant data, generate intuitive views, and feed insights back into the network.

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How to Pinpoint NYC’s Most Dangerous Driving Hours Using Data

When is it safer to drive in New York City?

Using GraphXR and motor vehicle collision data, we mapped crash patterns across every hour and day of the week. Our WeekDial visualization transforms temporal and geographic data into actionable insights for urban traffic safety.

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Understanding the Two Sides of Infostealer Risk: Employees and Users

Infostealer malware dominates today’s cyber threat landscape. Designed to extract credentials, cookies, session tokens, autofill data, and other forms of digital identity, infostealers operate silently, persistently, and at industrial scale. There are two critical vectors of risk: employee-driven and user-driven infections. Yet many organizations treat these threats uniformly, without differentiating between them.

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Accelerating Supply Chain Insights with Puppygraph & Kineviz GraphXR

PuppyGraph’s high-performance query engine transforms relational data into a graph in under 10 minutes—no need for a graph database. When combined with GraphXR’s advanced visualization and analytics, this powerful collaboration unlocks rapid insights, enabling faster decision-making and deeper exploration of your data.

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