Enterprise AI agents are failing in production because they lack a semantic backbone. Companies are spending millions on LLMs, vector databases, and agent frameworks — but without an ontology layer, these systems hallucinate, contradict business rules, and cannot be audited.

OntoArc exists to bridge that gap — through open-source tooling, applied research, and technical advisory. We focus on one class of problem: building the ontology architecture layer that makes AI agents production-ready.

Our approach — Extract, Model, Deploy — is grounded in formal ontological architecture, drawing from top-level ontology frameworks and applied to real enterprise domains. We call this discipline OntologyOps — the lifecycle management of semantic layers for AI agents.