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What you'll see

A full VectorOWL instance, pre-seeded and ready

Entity graph

Browse a pre-loaded systems graph — nodes, edges, and OWL-classified entities. Inspect attributes, follow links, and visualize topology in 3D.

OWL reasoning

Run SPARQL-like queries over the ontology. Trace subclass relationships, check satisfiability, and see how formal axioms constrain the model.

Vector search

Search by meaning, not keyword. Vector embeddings rank similar designs, requirements, and telemetry by semantic proximity.

Anchor constraints

Evaluate hard constraints that override probabilistic suggestions. See pass/fail results with severity levels and audit trails.

Run locally

One command to run the demo

The fastest way to try VectorOWL is with Docker. Clone the repo and start the container — it builds the UI and Rust backend automatically.

bash
git clone https://github.com/radsilent/VectorOWL.git
cd VectorOWL
docker-compose up --build -d
# Open http://localhost:8080
  • No installation or build step required
  • Pre-loaded demo scenario (car or aircraft)
  • Demo mode blocks destructive operations
  • CPU-only mode works without a GPU

Hybrid reasoning blend (illustrative)

VectorOWL mixes symbolic OWL constraints with embedding similarity. This slider does not call a server — it only illustrates how a tunable weight α biases the response toward symbolic versus vector pathways.

API status
Click to check API reachability.