Knowledge graphs are how agents remember and reason about the world — so we built one for the field itself. Drag the nodes, filter by domain, and click any concept to see what it means and how it connects.
Tip: drag nodes to rearrange the graph, hover to highlight neighbours, and use the search box to jump to any concept.
The same structure that makes this map readable is what gives production AI agents durable, explainable memory.
Vector search finds similar text; a knowledge graph stores facts and relationships an agent can traverse across sessions — the foundation of long-term agent memory.
GraphRAG lets a model follow chains of relationships to answer questions flat retrieval can't — "who depends on the service that owns this dataset?"
Answers can cite the exact entities and edges they came from, cutting hallucination and giving you an audit trail regulators actually accept.
We build production knowledge-graph and GraphRAG systems that give your agents real memory. Start with a free architecture review.