Neo4j launches Agent Memory: A graph-native memory system for AI agents
techNmak · x · 2026-08-18
Neo4j Labs released agent-memory, a graph-native memory system designed to provide memory, knowledge, and decision traceability for AI Agents.
- Key Features:
- Short-Term Memory: Stores conversation history and messages.
- Long-Term Memory: Builds a knowledge graph of entities and facts.
- Reasoning Memory: Tracks reasoning steps and tool usage, enabling traceability of decisions back to source data.
- Architecture: Built entirely on Neo4j, leveraging graph structures to naturally represent relationships between entities.
- Use Case: Allows agents to explain not just what they know, but why they decided what they decided, enhancing interpretability and context continuity.
Related event: Neo4j Launches Graph-Native Agent Memory for AI(2 posts)→
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