Wizdology Suite
Ontology & semantic intelligence
A standards-based semantic layer that connects enterprise data, defines shared meaning and gives AI a governed, machine-understandable business context.
How Smart Database turns data into semantic intelligence
From scattered records to connected meaning
01
Enterprise sources
Legacy systems, unstructured files and APIs.
02
Semantic mapping
Entity mapping and metadata alignment.
03
Ontology
RDF / OWL — meaning, rules and relationships.
04
Knowledge graph
Connected context and inference.
Powers → AI agents · GenAI · semantic search · advanced analytics
Standards-based modelling
- RDF and OWL models
- Classes, properties and relationships
- Taxonomies, vocabularies and semantic rules
Ontology management
- Create and maintain domain ontologies
- Reusable models and controlled vocabularies
- Versioning, validation and lifecycle governance
Knowledge graph
- Connect entities across multiple data sources
- Relationship-driven navigation and discovery
- Semantic search, inference and contextual linkage
AI & agentic context
- Ground GenAI and agents in enterprise semantics
- Improve retrieval quality and explainability
- Enable context-aware reasoning over business entities
Why ontology
The difference between an AI that guesses and one that knows
Without a shared model of your business, every agent and chatbot re-learns what a "customer", "case" or "citizen" means — differently each time. Wizdology defines it once, governs it, and grounds every AI answer in it.
Unified enterprise meaning
360° connected context
Higher-quality AI grounding
Reusable semantic assets
Interoperability
Governed knowledge
Works with
The semantic backbone of the platform
Give your AI a shared understanding of your business
See Wizdology model your domain and connect it to your data.