Zet: an open-source layer on Laya that knows when to ask a human

Confidence scores aren't error rates. Zet sits on top of Laya and marks every answer sure or unsure, using conformal prediction sets and a Learn-then-Test threshold calibrated per language, so the answers it automates stay within an error budget you choose (say 5%). On MASSIVE (human-labeled, 300 examples per language, 5% budget), it automated 84% of English and 80% of Swedish requests on a 6-scenario task, with 0 errors in 75 sure English answers. When the task got harder (18 scenarios), it automated nothing, while its prediction sets still contained the right answer 97-99% of the time. That refusal is the feature working. Runs locally on ONNX Runtime with no PyTorch, with a web interface for creating tasks, up labeled examples, calibrating, and reviewing unsure answers. Apache-2.0, built on Laya (not endorsed by its authors).