Ontology & semantic intelligence
A standards-based semantic layer that connects enterprise data, defines shared meaning and gives AI a governed, machine-understandable business context.
From scattered records to connected meaning
Enterprise sources
Legacy systems, unstructured files and APIs.
Semantic mapping
Entity mapping and metadata alignment.
Ontology
RDF / OWL — meaning, rules and relationships.
Knowledge graph
Connected context and inference.
From connected sources to grounded answers
Watch how Wisdology maps enterprise data to an ontology, links every record into a knowledge graph, and lets people and AI agents ask questions in plain language.
- Connect databases, APIs and documents
- Model classes, properties and relationships
- Search the knowledge graph in plain language
- Publish grounded answers as an API
Product preview. The Wisdology portal is coming soon.
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
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. Wisdology defines it once, governs it, and grounds every AI answer in it.
The semantic backbone of the platform
Give your AI a shared understanding of your business
See Wisdology model your domain and connect it to your data.