A next-generation AI ontology, semantic web, and knowledge graph platform built for the future of artificial intelligence, data reasoning, and structured machine knowledge systems.
Email: admin@coreontology.com
CoreOntology is built to unify ontology engineering, knowledge graphs, semantic AI, and LLM-based reasoning systems. We focus on turning unstructured data into structured semantic models that machines can understand, reason over, and integrate into real-world AI systems such as agents, search engines, and enterprise intelligence platforms.
Generate OWL/RDF ontologies from plain text using AI.
Text → OWLAICreate structured knowledge graphs from websites, text, or datasets.
GraphRDFConvert OWL/RDF models into Neo4j property graphs.
Neo4jGraph DBBuild RDF schemas visually or via structured AI prompts.
RDFSSchemaDetect inconsistencies and logical errors in OWL ontologies.
ValidationDebugCompare ontology versions and track semantic changes.
VersioningComparePerform logical reasoning and inference over structured knowledge.
InferenceLogicConvert websites into entity-based SEO structures for Google Knowledge Graph.
SEOEntitiesInteractive visualization of semantic networks and RDF graphs.
VisualizationGraph UIConnect LLMs with structured ontologies for grounded AI responses.
RAGAI AgentsAutomatically repair broken OWL/RDF structures and schema conflicts.
Auto-FixDebugGenerate industry-specific ontologies (finance, healthcare, ecommerce).
TemplatesIndustryConvert natural language into SPARQL queries.
SPARQLQuerySearch semantic models across multiple ontologies and datasets.
SearchIndexExtract structured entities from text for ontology mapping.
NLPEntitiesConvert ontologies into vector embeddings for ML and AI models.
EmbeddingsAIMap relational databases into ontology-based structures.
ETLMappingCreate AI assistants powered by structured semantic knowledge graphs.
AI AssistantRAGWe aim to become the leading platform for semantic intelligence systems, where structured knowledge, ontologies, and AI converge. Our goal is to make machine reasoning accessible, automated, and scalable for developers, enterprises, and researchers worldwide.