AI models that
never hallucinate.

Built on ontology, not statistics. Deductive reasoning through an Aristotelian logical spine, determining necessity in a conceptual space.

Coherence by construction.

  1. Surface

    Empirical Skin

    A small learned model with perception, parsing, world-familiarity.

  2. Kernel

    Conceptual Space

    Convex regions over quality dimensions. Kinds as objects, predication as inclusion. Composition is tensor product on a symmetric monoidal category.

  3. Kernel

    Ontological Kernel

    Seven axiom classes organized into verification layers: being, identity, causality, finality, essence, potentiality, non-contradiction.

  4. Kernel

    Logical Spine

    Admissibility and necessity as morphism filters across the kernels. Derivations factor through the spine. Inadmissible morphisms are refused.

  5. Output

    Gated Generation

    Only logically necessary and admissible morphisms close. Response generated based on the conclusion.

100.0% resolved.

Model% Resolved% AlmostCallsCost
Synesis100.0%0.0%42$1.02
Claude Opus 4.70.0%3.0%93$3.81
Claude Opus 4.60.0%2.5%260$11.38
Claude Sonnet 4.60.0%1.6%475$27.09
Claude Haiku 4.50.0%0.0%124$0.80
Gemini 3.1 Pro0.0%0.0%94$1.51
Gemini 3 Flash0.0%0.0%89$0.33
GPT 5.40.0%0.0%16$0.33
GPT 5.4 mini0.0%0.0%18$0.04
GPT 5 mini0.0%0.0%15$0.03

ProgramBench. % Resolved = fraction of 200 tasks where all tests pass. % Almost relaxes to ≥95%.

Research.