Black vs Kranth

A black-box evaluation of how AI-generated tests find functional bugs in live APIs.

Paste version A. The same people hit it, we rewrite B, they hit B. Ship the version they could not kill. Synthetic audiences as infrastructure.

About Black

A black-box evaluation of how AI-generated tests find functional bugs in live APIs. The harder question is whether those tests find bugs. Each system receives only a JSON schema and one valid sample payload, then must generate API test cases that expose failures in a live reference API. The evaluation uses APIEval-20 v1.0, a black-box benchmark contributed by KushoAI. Because KushoAI is also one of the evaluated systems, this report includes the methodology, workflow definitions, repeated-run setup, and robustness checks so readers can understand where the performance difference comes from.

About Kranth

Paste version A. The same people hit it, we rewrite B, they hit B. Ship the version they could not kill. Synthetic audiences as infrastructure. Kranth stress-tests ideas against adversarial AI personas before strangers do. Kranth is not a market forecast and not a replacement for real users. It is a pre-build, pre-spend stress test so teams find the objection while changing direction is still cheap. Four modes: Simulations (A then B on the same seats), Debate (structured formats including 1v1, panel, town hall, press, and pre-mortem), Recon (web-grounded research swarm with citations and PDF), and Interview (you are the subject).