Development

local-jev

by Nate Ritter
Newv1.0.1
$9one-time
License key required after purchase

About this skill

Make Laya trustworthy. Fit its confidence to your own labeled data, keep the decisions it gets right local and free on Apple Silicon, and send only the ones it does not know to hosted Jev (TypeSafe System One) or any OpenAI-compatible LLM. Includes a Jev-compatible local server (laya-mlx), per-type temperature calibration with before/after ECE and accuracy, confidence thresholds for a target accuracy, an escalation-rate and cost report, a fail-open TypeScript decide() client, and a playbook to find LLM calls that are really classifications. Use for ticket routing, yes/no gates, rubric scores, replacing prompt-and-parse LLM classification, cutting Jev or LLM spend, and private offline typed decisions.

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