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)→
More from coding & agent
- 4-dev side team makes $3k/month, wants Claude + MCP to run $3k/month ads — Elegant_Tourist_8313 · 2026-08-18
- Google One vs. Code Assist: small business owner puzzles over the 1,500 daily request cap — innovaldragon · 2026-08-18
- 2,500 RSVPs for 250 Seats: OpenAI Codex Meetup Seoul Sets Record — gabrielchua · 2026-08-18
- Running Qwen 3.8 27B locally for 8+ hours: 131M tokens, ~$650 saved vs. Opus API — illgettheownerforyou · 2026-08-18
- Codifying a Business into Agent Skills So the Founder Stops Being the Bottleneck — evielync · 2026-08-18
- WeCom Opens 10 Office Modules to AI Agents via MCP — aigclink · 2026-08-18