questions: { refund: boolean, spam: boolean, }
simple-jev
Turn any open model into a classifier/jev endpoint

Every project here really calls Jev in its source · refreshed daily
questions: { refund: boolean, spam: boolean, }
Turn any open model into a classifier/jev endpoint
questions: { refund: boolean, }
This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
questions: { route: choice, urgent: boolean, severity: score, }
Nemotron Diffusion Decision Lab
questions: { model: choice, effort: choice, is_followup: boolean, }
Local proxy that picks the Claude model and effort per message using TypeSafe Jev. Routes subagents, leaves your cached main chat alone.
questions: { difficulty: score, needs_reasoning: boolean, stakes: score, // +5 }
Shift every LLM call to the cheapest model that can handle it. Routing decided by TypeSafe Jev in ~180 ms. No training data. Policy in plain YAML. TypeScript and Python.
questions: { is_billing: boolean, }
Build versioned judgment functions on TypeSafe's Jev once, then call the same published version from your backend over HTTP and from coding agents over MCP. The vendor key stays on your machine.
questions: { hallucination_sensitive: boolean, }
Type-safe model router. Jev (System One) banks each request to a typed catalog route.
questions: { tier: choice, is_greeting: boolean, }
Jev (TypeSafe) model router on the Vercel AI Gateway
questions: { same_intent: boolean, }
Skip expensive LLM calls when TypeSafe Jev says same intent. OpenAI-compatible local cache proxy — npx @kushalicious/jevcache
questions: { eligible: boolean, }
AI gateway that validates before it executes: Lead plans, JEV validates, Worker generates. Local-first control plane, 359-provider catalog.