Ontology-Driven Data Intelligence.
Your data, mapped the way your business actually thinks.
Overview
Why Ontology-Driven Data Intelligence exists.
AI becomes useful when it understands the entities, relationships, and rules that shape how a business actually works. Most enterprise data has none of that context — it's columns and rows with tribal knowledge trapped in people's heads.
Our ontology layer profiles your data estate and maps it into a living business graph: customers, products, obligations, exposures, and how they relate. That graph becomes shared context for every downstream system — Vibalitics signals get richer, Zorat agents make fewer wrong turns, and AI Business OS gets its unified context from here.
Core capabilities
What it does.
Automated profiling
Scans warehouses and lakes to infer entities, keys, lineage, and quality issues.
Business ontology
Maps raw schemas into the entities and relationships your operators actually use.
Context API
Serves the graph to models, agents, and applications as governed, queryable context.
Living documentation
The ontology stays current as schemas evolve — no more stale data dictionaries.
Applications in the field
Where we use it every day.
01
Entity resolution for fraud
Accounts, devices, merchants, and beneficiaries resolved into one identity graph — coordinated fraud rings surface as connected structures, not isolated alerts. Feeds Vibalitics fraud signals directly.
02
Customer 360 & exposure
One customer entity across every product line — total exposure, relationship value, and next-best-action computed on the graph instead of stitched across six systems.
03
Clinical knowledge grounding
EHR fields mapped to clinical concepts so documentation and prior-auth agents cite the right evidence — diagnosis, order, and outcome linked the way clinicians reason.
04
Catalog & demand graphs
Products, attributes, substitutes, regions, and seasonal events as a connected graph — the feature layer behind demand forecasts that survive festival season.
05
Agent grounding
Zorat agents query the ontology before they act. Grounded context means fewer wrong turns, and every agent decision cites the graph path it reasoned over.
06
Lineage & quality profiling
Continuous profiling catches broken keys, schema drift, and stale documentation — the data estate stays mapped as it evolves, not as it was two years ago.
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