Where Formal Reasoning Meets Generative Intelligence
Trivyn combines ontological reasoning with LLMs to rapidly turn messy data into structured, queryable knowledge.
Trivyn combines ontological reasoning with LLMs to rapidly turn messy data into structured, queryable knowledge.
LLMs are powerful but unreliable. They generate plausible answers with no guarantee of correctness. Formal reasoning provides guarantees but can't handle messy, unstructured data.
Trivyn is a neurosymbolic AI platform that uses LLMs where they excel (understanding natural language), and formal OWL reasoning where rigor matters, ensuring your knowledge is logically consistent and queryable.
Import CSV, SQL, or JSON and Trivyn maps it to a rigorous upper ontology framework (BFO-2020 + Common Core Ontologies). Your data gets standardized definitions for people, organizations, events, artifacts, and more automatically.
LLMs handle semantic understanding and entity resolution. Rule-based extraction captures structure. OWL validation ensures logical consistency. The result: production-quality knowledge graphs from messy source data.
LLMs recognize entities and understand intent from your questions. Symbolic graph traversal walks your knowledge graph to find precise answers. You get the flexibility of natural language with the rigor of structured reasoning.
Interactive graph networks reveal relationships. Automatic detection of coordinates and WKT geometries plots your data on maps. Explore entities, properties, and connections visually.
When you need fine-grained control, a full SPARQL query editor with auto-completion and syntax highlighting is always available. Ask complex questions across your entire knowledge graph.
Building: LLMs interpret your data while Growl, an OWL 2 RL reasoning engine with Z3-checked contracts and 97% rule coverage, performs consistency checking, detects unsatisfiable classes, and enriches your graph through inference. Trivyn's pipeline detects violations before they reach your knowledge graph.
Querying: Natural-language questions are parsed by LLMs for entity and intent recognition, then answered through deterministic graph traversal: results grounded in structure, not hallucinated.
Full control over your data, AI, and reasoning infrastructure
Runs entirely on your infrastructure. Deploy on-premises, in your private cloud, or in air-gapped environments. Single binary, just point it at your LLM provider.
Use Ollama for fully local AI with no external API calls, perfect for air-gapped deployments. Or connect to OpenRouter or OpenAI. Switch providers at runtime without server restarts.
Your data never leaves your servers. API credentials encrypted at rest. Configurable map tile servers for fully internal deployments, no calls to external services required.
From data import to neurosymbolic reasoning to interactive exploration: see the full workflow
Click nodes to explore entity types, properties, and relationships with detailed metadata panels
View SPARQL results as interactive graphs, plot geospatial data on maps, or view and export raw data
Explore graph data with AI-powered natural language queries
Generate formal ontologies from data using hybrid AI with rule-based extraction and LLM semantic alignment
One researcher can build production-quality knowledge graphs. No team, no months of setup and knowledge engineering. Just your data and Trivyn.
BFO-2020 upper ontology + CCO mid-level ontologies + your domain ontologies + OWL reasoning = immediate semantic interoperability
Import from CSV, JSON, RDF, and SQL databases. Trivyn meets your data where it is.
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