A Tour of the Neo4j Agent Memory Service (NAMS)

The Neo4j Agent Memory Service (NAMS) offers a graph-native memory layer for AI agents, addressing the limitations of current systems that forget previous interactions. NAMS provides persistent, structured memory through a managed cloud service, utilizing a Neo4j Aura graph database with native vector indexes. It offers three types of connected memory: short-term (conversation), long-term (knowledge graph of entities and relationships), and reasoning (record of the agent’s steps and tool calls), all integrated into a single system. The service includes features such as entity extraction, deduplication, embedding, background compression, and context retrieval, and it supports customizable ontologies for different domains. NAMS is in its experimental phase under Neo4j Labs, encouraging user feedback to enhance the service. It also integrates with various platforms like Salesforce, GCP, AWS, and Microsoft, aiming to provide a durable memory framework for AI agents.

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