It Just Got a Whole Lot Easier to See What’s Really Happening in Azure Data Explorer

Tabular data can be hard to understand. You might have millions of rows of data and no clear view of the connections. You might have a feel for what is connected. But how do you see the relationships, patterns, and outliers clear as day? With Graphistry + Microsoft’s Kusto Graph, it’s now nearly instant – and visual.

We are pairing with the people behind Microsoft Kusto on a new integration bringing together the speed and scale of Azure Data Explorer’s Kusto Graph engine with Graphistry’s lightning-fast, GPU-powered visual graph exploration. That means security teams, fraud analysts, SREs, and data scientists can finally ask deep, relationship-based questions about all their data in Kusto – and actually see the answers unfold interactively, even across billions of events.

Whether you’re hunting threats, investigating outages, or mapping fraud rings, you can now query rich graph structures using familiar Kusto Query Language (KQL), and instantly pivot into rich, interactive point-and-click visual investigations powered by Graphistry. 

Graphistry’s new genAI-native Louie.ai platform enables you to vibes investigate all your Kusto data in natural language, and even create long-running agentic investigation automations from simple text. For developers and data scientists, our popular Python, JavaScript, MCP, and REST APIs mean you can bring these capabilities to your workflows like Jupyter notebooks, Databricks dashboards, and your own apps and AI tools.

What makes it powerful:

• Scales to billions: Native graph support in Kusto handles high-volume telemetry, logs, and events.
• Visual at GPU speed: Graphistry renders millions of nodes and edges interactively, helping analysts follow connections in real time and drill down with many  integrated views.
• Natural-language insights: With Louie.AI, you can even ask graph questions in natural language and easily prompt smart many-step investigation agents.
• Plug into your stack: Embed into your existing workflows or use standalone UIs – Azure-native support, Python/JS/MCP/REST APIs, and notebook-friendly – no massive pipeline rewrites.

Fast real-world wins:

We have created a jupyter notebook graphistry_ADX_kusto_demo that shows you how to import a CSV into Azure Data Explorer. Here you can quickly create a persistent graph.  We show how to export that graph into a Graphistry visualization. All you need is a Microsoft account and a free Graphistry Hub account to test it on your own.

The notebook takes a look at a dataset of authentications where a subset of the authentications are from verified red team activity. We have previously used this dataset to show the power of UMAP to cluster your cyber activity.

Graphs bring an entirely new way to see your data. When your job depends on understanding how things connect, this changes everything.