The Graph
Engine for AI.
One engine. Three AI workloads.
GraphRAG
Standard RAG retrieves text chunks by similarity. GraphRAG traverses a knowledge graph to follow multi-hop relationships across entities — connecting information that similarity matching can't reach. Memgraph executes the entire retrieval pipeline as a single atomic Cypher query.
AI Memory
LLMs are stateless. Vector-based memory retrieves what sounds similar — not what's structurally relevant. Memgraph stores and connects three types of long-term memory — semantic, episodic, and procedural — as a unified graph that any AI system can query in real time.
Agentic AI
The core question for any agent is: what should I do next? A reasoning graph makes the answer explicit — an action space where graph algorithms find the highest-scoring path from current state to goal. Memgraph is the agent’s real-time reasoning engine.
Auditability as structure.
When the agent acts, the traversed path is an inspectable trace. Alternative paths can be scored and compared. The basis for the decision is examinable through graph structure and edge scores — not through interpretation of token probabilities.
One engine. Two workloads.
Trusted in production.
Start in minutes.
curl -sSf "https://install.memgraph.com" | sh
iwr https://windows.memgraph.com | iex
