The Cyber Story
How a carrier's policy wordings become a governed cyber ontology with NAICS↔ISO crosswalks and a cited coverage answer — in hours instead of the weeks a data-modeling team spends by hand.
In developmentA governed map of meaning from your industry documents — measured for accuracy, signed off by your experts, and traceable to the source line.
The same entity is described in incompatible systems, and the rules that connect them live only in PDFs no software can read. In healthcare, one diabetic patient is four different records at once.
The result is miscoded claims, denied bills, missed care, and quality measures that cannot be computed. The same shape of problem shows up wherever meaning is trapped in documents — insurance policies, regulations, data dictionaries, product specs.
A multi-tenant engine wrapped around a five-pass LLM extraction pipeline. It surrounds your systems of record — it reads, it never writes back — and emits portable, open artifacts that load into any graph or semantic platform.
Every run is scored for precision, recall, and F1 against a gold standard, with a quality gate in CI. The number is the differentiator — almost nobody else measures.
Concepts, relationships, and answers each carry a citation and a confidence score. The cited GraphRAG layer turns "the model said so" into a defensible, auditable artifact.
SMEs approve, flag, correct, and sign off — diff by diff, fully audited. The autonomy dial automates construction, never governance. The standard changes only on sign-off.
OWL, SHACL, SKOS, JSON-LD, and Neo4j Cypher — each W3C-validated on every run, loading into GraphDB, Stardog, Neptune, Collibra, or Neo4j.
Grounded in the standards your sector already uses — FIBO, NAICS, NIST, ISO-ACORD, ICD-10, FHIR — so the model is credible, not invented.
Point it at a different corpus and adapter and it produces the same governed result. Proven cross-domain on insurance and healthcare with one pipeline.
From a folder of documents to a published, queryable standard — with the human in control at every gate.
Choose the grounding standards. Open standards take the fast path; licensed terminologies are tracked in parallel and kept local under their license.
Run the five-pass extraction — concepts, relationships, taxonomy, crosswalks, constraints — build the canonical model, and assemble the gold candidate.
Run fit and gap against your own corpus, then SME diff-review and steward sign-off. The machine's draft becomes a trusted, versioned standard.
Publish the consumer API and query the governed graph. Applications and AI assistants get the same source-cited answer, every time.
Insurance is governed and measured with a frontier model. Healthcare is an active build toward an NLM SBIR Phase I application — preliminary numbers, labeled as preliminary.
We report measured numbers as measured. Where a funded target is not yet met before award, we state the honest value and why it is a Phase I deliverable. Synthetic data is labeled as synthetic.
A modest-but-measured number with a roadmap beats an unmeasured claim that it is great. Every artifact OntoGen emits is validated against the W3C standard validators on every run.
Healthcare build supports an NLM SBIR Phase I application. No PHI anywhere; licensed terminologies stay local under the UMLS license.
Each story walks one real patient or one real policy through all seven layers, from a folder of PDFs to a safe, cited answer at the point of use.
How a missed kidney risk becomes a caught one. One patient, four broken vocabularies, and the governed map that makes her care safe, her code precise, her claim defensible, and her quality measure computable.
Read the story →How a carrier's policy wordings become a governed cyber ontology with NAICS↔ISO crosswalks and a cited coverage answer — in hours instead of the weeks a data-modeling team spends by hand.
In developmentOntoGen is a jagat.ai product, founder-led, with a network of consultants. If you are exploring a semantic-layer or knowledge-graph initiative, or evaluating an accelerator for a carrier engagement, get in touch.
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