Visualise cause and effect across a battlespace — events, intel, and actors connected by typed causal links you can filter, trace, and extend.

The Intel Causal Graph

The Intel Causal Graph is a full-page, node-link visualisation of a battlespace's events, intel items, and actors, connected by typed causal links. Where the map shows you where things happened, the graph shows you how they relate — the chains of cause and effect that turn a scatter of incidents into an explanation.

It's the tool you reach for when the question stops being "what happened?" and becomes "why, and what followed?"

Opening it

Two ways in:

⇢ Graph in the header opens the graph inside the right-hand workspace dock, alongside the live map — useful when you want to keep spatial context.
The full-page view at /graph gives the graph the whole screen for dense investigations.

Reading the graph

A directed node-link diagram:

Nodes are the entities — intel items, events, and actors — each drawn with a distinct shape so you can tell types apart at a glance.
Edges are typed causal links between them, colour-coded by type, with a legend down the left naming each.

Links come from two places, tracked separately in the stats: event links (the direct relationships you set between events — see Events) and causal-graph links (relationships modelled in the graph itself).

Controls

Across the top:

A battlespace selector — the graph is scoped to one battlespace at a time.
Node-type toggles with live counts — show or hide intel, event, or actor nodes to declutter.
A layout dropdown — the causal-flow layout arranges nodes to flow along cause-and-effect direction; other layouts suit different shapes of investigation.
A draw-link tool — click a source node, then a target, to draw a new causal link.

Down the left (legend & filters):

The link-type legend, where each type can be toggled off to hide those edges.
By Actor — filter to a specific actor's involvement.
A minimum confidence slider — hide low-confidence links to focus on the strong chains.
Live node and edge counts so you always know how much you're looking at.

Selecting a node

Click any node to open the detail panel with its full information. From there you can read into the entity and follow its connections outward — walking the chain link by link.

How to use it

The graph is at its best when you have a hypothesis to test:

Scope it to the battlespace you're working.
Filter to the actor or confidence level you care about.
Switch to the causal-flow layout to see the direction of cause and effect.
Trace the chain that leads to (or from) the event you're investigating.

Building event links as you work (see Events) is what makes those chains appear here — the graph is only as rich as the relationships you and the pipeline have established.

Where to next

Events — where event links originate.
Escalation & Predictions — the forward-looking complement to causal tracing.