What it is
OpenJev (Verdict) is an open-source post-trained foundational decision model for structured software workflows, inspired by TypeSafe AI's Jev and RLCD. It evaluates typed questions in a single forward pass, returning choices, scores, and probabilities with calibrated confidence.
How it uses Jev
Jev is used as a benchmark audit: the README reports a TypeSafe AI Jev benchmark audit and evaluates OpenJev on 231 public JevBench tasks. The README does not specify how Jev itself is invoked or integrated in code.
Primitives:choicescorenoul
Technique worth stealing
NLI sentence templating for candidate labels and auto-calibrator with per-k scaling.
Try it
Run the in-browser WebGPU playground (see README section).
Evidence
Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.
- Jev-centricyes0.79
- Shows a System One patternno0.32
- Handles uncertaintyno0.11
- Measuredno0.11
- Runnableyes0.69
- Worth recommendingno0.33
- Model replicayes0.94
- Problem scopescore on a 0–2 scale1.66
- About Jevyes0.93
Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.