Practitioners who have shipped ontologies where mistakes are expensive
OntologyForAI is an enterprise ontology and knowledge-graph consultancy. We bring regulated-industry semantic engineering to the organisations building — and buying — AI applications across the USA, Australia and Europe.
Make enterprise AI understand before it answers
AI is moving from chat to action. When agents read records, call tools and make recommendations, the cost of misunderstood meaning or over-shared data rises sharply.
We exist to give every AI application a precise, governed model of the business it serves — so it uses the right definitions, stays inside the data boundaries its users and regulators expect, and can always show its evidence. We do this with open standards, so the value stays with you.
- Business questions first
- Standards-aware engineering
- Vendor-neutral architecture
- USA · Australia · Europe
Ontology depth
OWL, RDF, SHACL, SPARQL and industry standards like FIBO, FHIR and ACORD.
AI delivery
GraphRAG, multi-agent orchestration, MCP tools and evaluation harnesses.
Regulated domains
Banking, wealth, insurance, healthcare and life sciences, manufacturing.
Research-grounded
Peer-reviewed work on ontology merging and semantic technologies.
Senior practitioners, not slideware
Every engagement is led by senior ontology architects and knowledge engineers who have delivered semantic platforms inside global banks, insurers, healthcare organisations and manufacturers.
Ontology architects
OWL, SHACL, SKOS and industry standards such as FIBO, FHIR and ACORD.
Knowledge engineers
Graph modelling, entity resolution, mappings and provenance at scale.
AI engineers
GraphRAG, LangGraph and CrewAI agents, MCP tools and evaluation harnesses.
Governance specialists
Privacy, access control and AI-risk alignment with regional regulation.
Our engagement commitments
Honest fit
If search, a glossary or plain RBAC solves your problem, we'll tell you — before you spend on an ontology.
Measured outcomes
Baselines and acceptance criteria are agreed in writing before build, and reported against at the end.
Your data, your terms
We can start with synthetic data. Real-data access, hosting and permitted use are agreed up front.