Collaborative, structured, intelligent — meet the future of knowledge graphs.
OpenOntology is a platform where intelligent systems don’t just act — they explain.
It transforms knowledge into a structured, versioned, and verifiable asset — no longer hidden in tribal memory or scattered docs.
At its core, OpenOntology unites four disciplines to make knowledge usable by both people and machines:
OWL, SHACL — formal structure, validation, machine readability.
Markdown, Git, CI/CD — knowledge as versioned, reviewable, and testable code.
AI that generates, improves, explains, and validates knowledge — grounded, not hallucinated.
Structured knowledge that can be queried, analyzed, and reused across teams and agents.
With OpenOntology, your company’s knowledge doesn’t live in people’s heads — it lives in a shared, evolving graph of meaning, accessible to humans and AI alike.
All knowledge is human-readable and versioned as Markdown with YAML metadata.
Submit and review knowledge via pull requests, with full CI/CD integration and history.
Generate, improve, and explain ontologies with integrated GPT-model support.
Export to APIs, GraphQL, DTOs; validate with OWL, SHACL; integrate with GitHub and agents.
Graph visualizations, history diffs, discussions, and annotations — built-in.
Designed for engineers: Markdown, Git, REST/gRPC, and schema-first thinking.
Unified formal models for roles, processes, and data. No more knowledge locked in people’s heads.
Catch ambiguities and duplications early using formal validation and human reviews.
Ontology becomes the shared contract between APIs, microservices, and teams.
LLMs reason based on structured, verified knowledge — not scattered notes or outdated docs.
Build a living knowledge graph that persists beyond individuals or teams.
Enable agents and systems to "understand" your domain and generate explanations or code.
OpenOntology unites four powerful domains into one elegant platform:
Based on OWL, RDF, and SHACL — precise, formal, and machine-verifiable.
Markdown, Git, CI/CD — versioning and automation are built into the core workflow.
AI helps generate, explain, and evolve knowledge. GPT supports reasoning and validation.
Ontologies live as readable, versioned, structured artifacts — integrated into engineering workflows.
LLMs grounded in ontologies reason over structured, validated knowledge — not vague or invented facts.
Ontologies are modular and reusable — define once, reference everywhere. Build scalable systems of meaning.
The result: versioned, reviewable, readable knowledge — usable by both humans and machines. Not just an editor. A platform for continuous evolution of collective expertise.