ontology

Graph-Native Infrastructure for Context and Accountable AI Systems

AI-native ontology engine: a Rust MCP server with tools for building, validating, querying, and reasoning over RDF/OWL ontologies. In-memory Oxigraph triple store, native OWL2-DL tableaux reasoner, SHACL validation, SPARQL, versioning. Single binary, no JVM.

Strwythura: construct an entity-resolved knowledge graph from structured data sources and unstructured content sources, implementing an ontology pipeline, plus context engineering for optimizing AI application outcomes within a specific domain. This produces a Streamlit app, with MLOps instrumentation.

[KDD 2026] MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation

Metronix Memory is self-hosted memory infrastructure for AI agents: MCP-native, local-model friendly, with hybrid RAG, a temporal knowledge graph and ontology layer, durable memory, freshness checks, and agent-scoped context

Domain-Aware Neurosymbolic Agent (Dana), an agent-native programming language

Cross-border e-commerce AI knowledge base, designed to be read by people and installed by agents. 69 trilingual guides, 878 structured prompts, a 94-entity / 318-constraint domain ontology, and 9 agent skills served over MCP. Factual claims are dated and CI-verified; prompts declare their data requirements and failure boundaries. CC0.