Heads up: All models on this page are in their early stages and should be considered placeholders. The underlying methodology is still being refined — take the specific numbers with a grain of salt.
The AI Process
How AI discovers, tests, and improves the pitch grading models — from podcast transcripts to production upgrades.
By the Numbers
Why We Show the Failures
About half of all tested features don't survive. We document them alongside the successes because the dead ends are often more instructive — CSW looked better than xRV by every per-pitch metric we measured, until we measured the right thing. Cascade+ was our most complex system ever, and direct regression beat it with a fraction of the infrastructure. The willingness to scrap significant investment when the data says so is what makes the process trustworthy.