A graph-native memory system for AI agents and context graphs. Store conversations, build knowledge graphs, and let your agents learn from their own reasoning — all backed by Neo4j.
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Updated
Apr 5, 2026 - Python
A graph-native memory system for AI agents and context graphs. Store conversations, build knowledge graphs, and let your agents learn from their own reasoning — all backed by Neo4j.
Lightning-fast data access platform designed specifically for AI agents
A production-ready MCP server that builds a world model for codebases, preventing hallucinations, repeated mistakes, and regressions in Claude Code.
A simple method for keeping your context and decisions in one place when working with AI. Markdown files. Works with any model.
Thesis: The Software Collapse Has Already Happened
Agentic Air Logistics Control Plane ingests real disruption signals (FAA NAS status, METAR/TAF, NWS alerts, OpenSky ADS‑B) for airports, builds a bi-temporal context graph, and runs a deterministic (12-FSM) multi-agent state machine to emit a governed decision packet with a gateway posture
Recursive learning framework, give any AI agent a self-improvement loop with memory. No fine-tuning, just API calls
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