Jev vs GPT-4.1 as synthetic survey respondents on Twin-2K-500. How you ask mattered more than which model you used.
Applications — page 32
Complete applications where Jev makes a product decision: routing, ranking, classification or approval.
2,602 active projects in this collection. All collections →
Table tennis vs. TypeSafe's Jev (System One). Every paddle move on the right is a live model decision — no local prediction, just a lookup table and a servo.
No project description available.
No project description available.
No project description available.
Jev-driven interfaces with on-demand diffusion visuals and constrained rendering.
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JEV core — the judgement primitive and harness for TypeSafe System One (Jev). Closed-set, fail-open, stdlib-only.
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Turn Any Open-LLM into a System-one Jev model
jevkit for JavaScript/TypeScript: static linter and shared record format for building on TypeSafe's Jev (System One) model. Unofficial.
jevkit for Python: static linter and shared record format for building on TypeSafe's Jev (System One) model. Unofficial.
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An attemt to recreate jev model on top of gemma
1,000 synthetic SaaS accounts, 6,000 constrained judgments from TypeSafe's Jev, and ordinary TypeScript deciding who needs a human today. TanStack Start on Bun.
GitHub Action + CLI: triage PRs with TypeSafe Jev (ready / needs review / risky) with confidence gates and jevcheck-friendly contracts.
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No project description available.
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Generate a landing page from one sentence: an LLM writes the copy, Jev makes the judgement calls, code owns the rules.
Minesweeper where deterministic logic does the provable work and TypeSafe Jev is consulted only when the board forces a guess.
👩🔬 Pilot of the decision model 'jev' from TypeSafe AI
Cloudflare Worker to check for profanity using TypeSafe Jev
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TUI harness orchestration with herdr and jev to efficiently distribute work across your coding subscriptions.
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Mop the slop out of your LinkedIn feed. Not an AI detector: a bad-writing detector. Chrome extension + Vercel server, powered by Jev from Typesafe AI. MIT.
No project description available.
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Claude reads the part of a large file that answers your question, not the whole file. A PreToolUse hook. Measured: -36% cost on the reads it fires on, no answer lost.
Ruby client for Jev, TypeSafe's System One model: typed questions, probabilistic answers. Zero runtime dependencies.
An empirical experiment fusing TypeSafe AI's non-autoregressive Jev model (System 1) with a high-performance 0x88 alpha-beta search engine (System 2). Includes live Chrome extension tracking, trust window fusion, and real-time telemetry, capable of defeating 1825 ELO bots.