Hypothesis
This entry runs no foundation model. Every finding below is quoted to the vendor’s own document, or marked not disclosed where the vendor publishes nothing.
Property-based testing library for Python — generates thousands of random test inputs to detect logical hallucinations like off-by-one errors and inverted conditions in AI code
No foundation model. Hypothesis does not run one, so this criterion does not apply and is excluded from the grade rather than counted against it. A property-based testing library for Python that generates and shrinks randomized test inputs against user-declared properties; the generation is algorithmic search, not model inference. Established from the product’s own public documentation and what it does. If that is out of date, tell us at right of reply.
Not yet assessed. We publish a sovereignty position only where the vendor documents one — we do not infer it from a domain or a company name.
Vannus publishes a nine-dimension trust framework — data sovereignty, training privacy, compliance posture, operational resilience, exit portability, and more. The heaviest criterion asks whether the tool builds its own AI or resells someone else's model; where the vendor discloses it, the grade cites the vendor's own documentation. No paid placements — scoring is walled off from affiliate revenue. See the methodology →