> ## Documentation Index
> Fetch the complete documentation index at: https://docs.xkat.space/llms.txt
> Use this file to discover all available pages before exploring further.

# Knowledge Graph Architecture

> How the Neo4j-backed knowledge graph is structured.

The knowledge graph is the backbone of xkat. This page explains how it's
structured behind the scenes.

## Nodes and relationships

* **Nodes** represent skills and concepts — the same nodes creators design in
  [Studio](/en/studio/knowledge-design) and learners explore in
  [3D](/en/learn/knowledge-graph).
* **Relationships** connect them. The most important is **`REQUIRES`**, which
  encodes prerequisites and gives the graph its learning order.

## Powered by Neo4j

The graph is stored and queried in **Neo4j**, a graph database well suited to
prerequisite traversal. When a course is published, its lessons are synchronized
into Neo4j as nodes joined by `REQUIRES` (and related) relationships.

## What the graph enables

<CardGroup cols={2}>
  <Card title="Personalized roadmaps" icon="route">
    [MyRoads](/en/learn/roadmap) traverses prerequisites to compute a path to your
    goal.
  </Card>

  <Card title="3D exploration" icon="diagram-project">
    The connected structure is rendered as an explorable skill universe.
  </Card>

  <Card title="Progress mapping" icon="chart-line">
    Completion is tracked against nodes, so mastery is visible on the graph.
  </Card>

  <Card title="Reusable knowledge" icon="recycle">
    Atomic nodes can be connected across courses into one coherent universe.
  </Card>
</CardGroup>

## Related

<Card title="AI control pipeline" icon="gears" href="/en/platform/ai-pipeline">
  How content gets into the graph reliably.
</Card>