Provides meaning to observations. The engine draws on ten AIREx sources — Property, Organization, and Opportunity Graphs; Knowledge Fabric; Historical Decisions; Digital Twins; Research; Forecasts; Policies; and Infrastructure — and returns a context graph with supporting evidence, missing context, and related entities. Context turns isolated facts into understanding.
Sources
10
Active
10
Context nodes
0
Edges
0
Gaps flagged
0
Presets
Load a scenario
Focus
Entity in question
Observations
Inputs from Perception
Active sources
10 / 10
Context graph
Run the engine to populate
Choose a focus entity, describe what is observed, pick which context sources to draw on, and press "Build context graph". AIREx returns a graph of related nodes with their roles, edges typed by relation (relationship, dependency, historical, semantic, cross-domain), historical precedents, dependencies with criticality, cross-domain links, semantic frames, evidence, gaps, and adjacent entities.
Context Engine™ produces meaning, not decisions. Observations come from the Perception Engine (EP-067); reasoning is performed by AIF (EP-066); decisions require an accountable human.