context-graphs

Graph-Native Infrastructure for Context and Accountable AI Systems

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

world-model-mcp is a signed audit memory server for AI coding agents, delivered as an MCP tool. Every event Ed25519-signed and Merkle-chained; offline-verifiable against pinned public keys. Hosted platform with hybrid post-quantum signing at etch.systems.

Native agent-graph runtime written in C++20

Thesis: The Software Collapse Has Already Happened

A simple method for keeping your context and decisions in one place when working with AI. Markdown files. Works with any model.

TrustGraph's web UI, built with React 19, TypeScript, and Vite - includes context graph UX

Build graph-native context graphs and knowledge models for AI systems with deterministic reasoning, decision intelligence, and full provenance—open source, self-hostable, and auditable.

Deploy TrustGraph in an OVHcloud Kubernetes cluster using Pulumi

Recursive learning framework, give any AI agent a self-improvement loop with memory. No fine-tuning, just API calls