Decision Models / Jev

HOSTED

Jev

By TypeSafe AI · Released 15 Sep 2026

The model that named the category. A hosted API: send your app's state plus typed questions (Choice, Score or Noul) and get a probability back for each answer. It generates no text, and its weights are not public.

Facts

Price
$0.042 per million input tokens; output free · Compare prices
Latency
70–500 ms end to end (TypeSafe-reported)
Version
jev-1.13 is the stable release; jev-1.14 has been the preview build since 14 Oct 2026
Context
32,000 tokens (per OpenRouter's guide)
Access
Launched in early access; also via OpenRouter

Claims and sources

Links

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Related projects

Ultra-fast browser agent

Source: browser-use/jev-ultrafast ↗

Zurich to London on Google Flights in 7.1 seconds, including model calls, generated text, browser work and loading waits. Swapping to a decision model took median task time from 9.450s to 7.092s and median browser protocol calls from 1,092 to 101.

One natural-language goal, on the real web, at 1x speed. Maker-reported: three repeats of one task on one browser profile.

  • 7.09 smedian task, down from 9.45 s
  • 101browser calls, down from 1,092

browser-use · ★ 23,396 · MIT · Jev

  • browser
  • agent

Figures from the project's own README and docs/performance.md. The maintainers note this is three repeats of one task on one browser profile, not a general benchmark.

Source: GitHub → Source: Measurements →

Jev as a second pair of eyes for Claude Code

Source: Civalski/claujev ↗

A Claude Code plugin that asks Jev short typed questions while Claude works: how big is this request, is this command destructive, was the work really done. It suggests an effort level per request, and in enforce mode a confident check can block a "done!" when the work looks incomplete.

Civalski · ★ 4 · MIT · Jev

  • coding
  • agent

Sentence to typed query plan

Source: saembit/jevquery ↗

A TypeScript library where Jev picks the table, columns, filter, order and limit from what the schema offers, so it can choose a column but never write a query. Drizzle, Prisma or a SQL builder turns the plan into a real, parameterised query.

saembit · ★ 0 · MIT · Jev

  • sql
  • typescript

Pet shop catalogue with evidence

Source: jeromtom/petsona-catalogue-ai ↗

Tags each pet product's species, life stage and allergens from the store's own text, asking Jev or Laya one typed question per value: supported, contradicted, unknown or conflicting, with the source sentence attached. Merchants can approve, correct and lock tags, or let a validated policy accept them automatically. A hackathon entry for AIBoomi Startup Weekend Kochi, 23-24 Oct.

Jerom Palimattom Tom (Rexin Dynamics) · ★ 0 · MIT · Jev, Laya

  • e-commerce
  • shopify

Politicians by Jev

Source: n8peace/politiciansbyjev ↗

Ask a question and Jev, via Vercel AI Gateway, gives each of 100 well-known American politicians a yes/no probability; the faces above the threshold float up out of a physics pile.

n8peace · ★ 0 · MIT (code); portraits under their own licences · Jev

  • fun
  • web

Live interview checklist

Source: ByronDarlison/call-coach ↗

A macOS app that transcribes both sides of a call on your Mac with Whisper while Jev ticks off each of your questions once it has been answered, notes which question you just asked, and flags surprising answers for a follow-up. The maker puts Jev's cost at about 1 to 2 US cents for a 45-minute interview.

Darlison Holdings · ★ 0 · MIT · Jev

  • meetings
  • mcp
  • local

Voice tutor grounded in a textbook

Source: balajibankapur/textbook-voice-tutor ↗

Answers a seven-year-old's spoken questions from one scanned Grade 2 textbook chapter. Jev decides whether each new question can be answered from the chapter and, with the optional verifier on, whether the drafted answer's claims are supported by the retrieved passages; common questions are matched to cached answers. On the maker's 14-question test, the decisions API cut average answer time from 4.1 to 1.7 seconds and the cost of each gate call about 25 times, against the chat wrapper.

balajibankapur · ★ 0 · MIT · Jev

  • education
  • voice

Talk to your Mac in one sentence

Source: manikv723-jpg/JevVoice ↗

Speak several instructions in one run-on sentence and Jev picks each action from a menu of skills, and any app from those installed on your Mac, while you are still talking. Anything outside the menu goes to Claude for a proposed shell command, which waits for your approval unless you turn on trust mode.

manikv723-jpg · ★ 0 · no licence · Jev

  • voice
  • macos

A village run on Jev

Source: Dasge97/the-village ↗

A pixel-art village in the browser where Jev, via OpenRouter, chooses what each adult does for the next two hours, while fixed rules handle urgent needs, night-time sleep and children. The maker built it to test whether Jev's choices stay sensible and reflect each villager's personality.

Dasge97 · ★ 0 · MIT (code); CC0 1.0 (graphics and sounds) · Jev

  • simulation
  • game

PII discovery in plain SQL

Source: senthilsweb/jev-pii ↗

A DuckDB function that asks Jev typed questions about each database column: is it personal data, which kind, and whether GDPR, CCPA-CPRA, HIPAA, LGPD, PIPEDA or DPDP apply. Whether to keep, mask, hash or drop it is decided by code, not the model, and a failed call sends the column to review. Also runs in the browser.

senthilsweb · ★ 0 · Apache-2.0 · Jev

  • data
  • duckdb
  • compliance

Search evaluation with Jev as judge

Source: rickcrawford/jev-relevancy ↗

Grades search results with Jev on a four-level scale, checked first against Amazon's human-graded shopping queries, and stores runs, results and judgments in DuckDB with the metrics computed in SQL. The author recommends checking it against at least 300 of your own labelled pairs before trusting it on another domain.

rickcrawford · ★ 0 · MIT · Jev

  • search
  • evaluation

decisions, an R package and web app

Source: fmegahed/decisions-space ↗

A Hugging Face app built on the R package decisions: upload a set of images or texts, ask Jev one question about each, and get every answer with its probabilities plus the R code to repeat the run. Visitors need no key or account; runs are checked against estimated session and daily budgets.

fmegahed · ★ 0 · MIT · Jev

  • r
  • images

Android notification triage

Source: KoheiTakada/QuietFlow ↗

An Android app that can use Jev to sort notifications into five classes, from action required to hide, alongside local safety rules and corrections it learns from you. It starts in observation mode and never cancels notifications there; Jev is opt-in with your own key.

KoheiTakada · ★ 0 · MIT · Jev

  • android
  • notifications

West Philippine Sea Watch

Source: gianviterbo/wps-watch ↗

A public monitor of the West Philippine Sea with live ship positions, Sentinel-1 radar passes and Global Fishing Watch events. Jev answers four questions about each item from 13 news feeds, and two of them, whether it serves a Philippine reader and whether it carries PRC state framing, decide whether it is shown or held back. Live at wps.gdgt.link.

gianviterbo (Gadget Pilipinas) · ★ 0 · Proprietary (contact Gadget Pilipinas for reuse) · Jev

  • news
  • maps
  • monitoring

Tetris Arena

Source: arndth/tetrisarena ↗

Jev, SAP-RPT-1, LLMs and a 15-line heuristic play Tetris on the same pieces and candidate moves, with live cost tracking. In the maker's 50-piece race Jev and the heuristic both cleared 19 lines and the others 18, a tie within noise; the difference was speed and cost.

arndth · ★ 0 · MIT · Jev

  • game
  • comparison

Ants that draw your picture

Source: scalefreegan/jev-ants ↗

Each ant is a Jev agent that sees the cells around it and its neighbours' headings and decides which way to move and whether to settle. A thousand small decisions turn a random scatter into a word or an uploaded picture; the maker puts a word at about fifteen seconds and seven cents.

scalefreegan · ★ 1 · MIT · Jev

  • art
  • swarm

Decision models as tool routers, measured

Source: Daewooki/decision-agent-lab ↗

Calls Jev, OpenAI's Decisions API, Upstage Solar Decide and local Ollama models through one interface and logs version, latency, tokens and cost. On picking the right one of 12 tools for 40 Korean and English requests, the maker measured Jev 1.13 at 40 of 40 and OpenAI Decisions at 0.90, against 0.85 for a generative model choosing directly.

Daewooki · ★ 0 · MIT · Jev, Decisions API, Solar Decide, Nimble

  • agent
  • benchmark

Terms of service checker

Source: shohei81/jev-tos-checker ↗

A Chrome extension that splits the terms of service on the page into clauses and has Jev check each for eight kinds of one-sided term, from selling your data to forced arbitration, marking only clauses that go well beyond what major services do and showing each next to the original text. The maker says it is not legal advice.

shohei81 · ★ 0 · MIT · Jev

  • browser
  • extension
  • legal

CI failure triage

Source: tejred213/ci-triage ↗

Jev reads each failed test and decides the cause: environment or timeout, flaky assertion, genuine regression or API contract mismatch. Code re-runs the build only when every failure would be fixed by re-running (three attempts in all by default), gives flaky tests a low-priority ticket as well, and files tickets for real failures with the test's owner.

tejred213 · ★ 0 · no licence · Jev

  • ci
  • devops

X spam blocker

Source: bit-cook/Jev-X-Blocker ↗

A Chrome extension that hides spam and noise in X posts and replies by combining Jev's probabilities for rules you write in plain language with local signals, and decides locally what to hide. Everything hidden can be restored in place, and if the API fails, posts are shown.

bit-cook · ★ 1 · MIT · Jev

  • browser
  • extension

UI tests written in plain English

Source: andletenkov/decisium ↗

Write test steps as plain-English Gherkin and Jev picks the element, action and check for each one from options Decisium reads off the page; code, not the model, decides whether a step passed. Resolved steps are recorded so CI can replay them with no model calls.

andletenkov · ★ 1 · MIT · Jev

  • testing
  • playwright

Which fixes clear most Intune noncompliance

Source: dallascrilley/intune-why ↗

Reads Intune compliance data from Microsoft Graph, groups failing devices by the setting that fails, and ranks fixes by how many devices each makes fully compliant. For custom settings its rules don't cover, Jev can optionally pick the remediation path. You can try a live demo with a sample tenant.

dallascrilley · ★ 0 · MIT · Jev

  • it admin
  • microsoft

Classified ads filter

Source: Aladincz/Jev-Content-Filter ↗

A browser extension that asks Jev about every ad on the Bazoš classifieds site against criteria you write in plain language, and collapses the ones that don't match. Other marketplaces and auction sites are planned.

Aladincz · ★ 0 · MIT · Jev

  • browser
  • extension
  • shopping

GitHub issues filtered in plain words

Source: BerriAI/better-backlog ↗

A local web page and CLI that reads a repo's GitHub issues and lets you filter them by typing a criterion, such as people blocked from upgrading. Each criterion is asked of a decision model through your TypeSafe key or a gateway; add another to narrow the list.

BerriAI · ★ 2 · MIT · Jev

  • tooling
  • web

Agent questions answered by Jev

Source: jflowers/opencode-auto-question ↗

An opencode plugin for autonomous runs: when the agent stops to ask the human a question, Jev (or an LLM, if you set one; the default tries Jev first) picks from the offered options. Below a configurable confidence (0.6 by default) it gathers context in a side session and decides again; below 0.35 the human answers after all.

jflowers · ★ 0 · Apache-2.0 · Jev

  • agent
  • coding

Unorphan: loose files filed into their projects

Source: sushrutkhandelwal/unorphan ↗

A local app you point at a messy folder like Downloads: it works out which of your projects each loose file belongs to, reading the README or CLAUDE.md in your code folders, and files it into a matching folder under your chosen output location. Nothing moves until you press Move, and one click puts it all back.

sushrutkhandelwal · ★ 2 · no licence · Jev

  • desktop
  • files

Nouli: multi-turn sessions for decision models

Source: nouli-ai/nouli ↗

Decision models forget everything after each answer; Nouli keeps a session. Type facts as you learn them and start a line with ? to ask a new question; earlier facts and answers stay in the history. A Rust CLI and library that can chain sessions into decision graphs, with Jev through its TypeSafe adapter or other providers.

nouli-ai · ★ 12 · MIT · Jev

  • cli
  • rust

Kariyer decision bench: Turkish job ads

Source: kubrakrcn/kariyer-decision-bench ↗

Written at Kariyer.net R&D to pull seniority, department and work type out of job ads. On 600 real ads with 7 questions each (4,200 decisions), Jev 1.13.0 scored 71.5% against 64.6% for the open tau-4b and 65.7% for a prompted 4B LLM. tau-4b was better calibrated (ECE 0.093 against 0.156), and it scored 95.7% on its own training data, which is why the author warns against benchmarking a model on the set it shipped with.

kubrakrcn · ★ 0 · Apache-2.0 · Jev, tau-4b

  • benchmark
  • turkish

layagrep: train Laya to search code

Source: gak4u/layagrep ↗

jevgrep finds code by asking Jev thousands of yes/no questions. layagrep records those questions on SWE-bench tasks and fine-tunes the open Laya to answer them locally, with no API key and no code leaving the machine. A smoke run on 400 held-out questions lifted file-navigation AUC from 0.79 to 0.94 (Jev 0.97), but declaration relevance stayed at 0.58 (Jev 1.00).

gak4u · ★ 0 · Apache-2.0 · Laya, Jev

  • code-search
  • fine-tuning

fastbrowse: a browser agent where Jev picks each action

Source: agent-labs-dev/fastbrowse ↗

An LLM plans, reads and writes; Jev picks each action from the controls indexed on the page, and code stops irreversible clicks without authorization. On 46 tasks run three times each against the hosted Browser Use agent, it passed 99.2% of runs to 96.3% and cost $0.0296 a run to $0.3180, 10.7x less, but was slower: 18.9 s a task to 15.3 s (published campaign release-0.7.1).

agent-labs-dev · ★ 155 · MIT · Jev

  • browser
  • agent

JEV Damocles: when a group-chat bot should speak

Source: ch7flyer/astrbot_plugin_jev_damocles ↗

An AstrBot plugin that decides whether a bot in a group chat should reply. It merges bursts of messages, separates conversation threads, then asks Jev four questions, batched into one request when the backend supports it (was the bot addressed, does it follow, should it reply, how urgent). For messages without a direct mention, quote-reply or poke, it uses a high and a low reply threshold alongside other checks, and scores in between can be reassessed later; those direct interactions can skip the gate. The README suggests a 3 to 7 day dry run first.

ch7flyer · ★ 0 · MIT · Jev

  • chat
  • bot
  • astrbot

JevRouter: Jev picks the next step, a policy decides

Source: HangChi/JevRouter ↗

An agent runtime where an LLM reads the task, one Jev call answers four typed questions (next action, risk, whether to confirm, whether to reason further) and a local policy engine decides what may run. On 53 versioned test cases it hit the expected action 92.5% of the time against 96.2% for an LLM baseline, at about 1.0 s against 4.0 s, and asked for confirmation on 16 of the 17 cases that needed it.

HangChi · ★ 0 · MIT · Jev

  • agent
  • runtime
  • policy

skill-tester: grading agent skills with Jev

Source: milesroxas/skill-tester ↗

An eval harness for agent skills: headless agent runs, code checks, Jev judge packs and blind human review; the generic pack asks one yes/no question per skill rule. Graded with the writing pack, the reference skill's v2 run matched its original benchmark's report within 2 points on every layer and in total.

milesroxas · ★ 0 · MIT · Jev

  • evals
  • agent-skills

Agastya: walking a document's outline to find answers

Source: cars3/agastya ↗

Retrieval that walks a document's table of contents, asking Jev one yes/no question per section, then ranks the sections it kept with EmbeddingGemma. On all 6,005 test queries of the public SearchTome release it returned 89.1% of gold sections at 3.6 sections per query, against 84.5% at 3 for EmbeddingGemma alone; its top-1 and top-3 recall equal the embedding model's. Jev alone, ranking flat, scored 54.2 top-1. It needs no training and runs on one 8GB consumer GPU, and failed upgrades are published too.

cars3 · ★ 0 · MIT · Jev

  • retrieval
  • search

Jev picks the move for a robot arm

Source: uhiron55/physical-ai-2026-advanced-1-final-assignment ↗

A course project where Jev chooses the transfer strategy for a CRANE+ arm in a Gazebo simulation, MoveIt 2 plans the path and ROS 2 controllers run it. In three episodes on authenticated Jev decisions with no fallback, Jev picked the home transfer at 0.94 to 0.96 confidence and all three placed the cube, 2.70 to 7.48 mm off target. These are scripted-teacher episodes; the README's separate learned-policy (ACT) tests are not reported as grasp success.

uhiron55 · ★ 0 · Apache-2.0 · Jev

  • robotics
  • ros2

jev-droid: Android automation with two models

Source: frederico-kluser/jev-droid ↗

Drives an Android emulator from plain language: DeepSeek V4.1 Flash decides the next step, and Jev triages each screen (loading, error, permission prompt) and guards actions before they run. The three-step demo in the README, Settings to Network to Wi-Fi, cost $0.00019 and took 21 seconds; every step saves its screen, decision, tokens and cost.

frederico-kluser · ★ 0 · MIT · Jev

  • android
  • agent

topic-gate: reset the chat when the topic changes

Source: tauseefau/topic-gate ↗

Asks Jev one question per message, 300 to 600 input tokens, to tell whether the conversation is on the same topic, a subtopic or a new one, and recommends a session reset only when a new topic wins clearly (p of at least 0.65 and 0.25 ahead), so you stop paying to resend a dead transcript. Checked against live Jev on related, unrelated and short messages.

tauseefau · ★ 0 · MIT · Jev

  • context
  • agent

pi-omarchy-cu: Linux desktop control for the Pi agent

Source: Paul-Yuchao-Dong/pi-omarchy-cu ↗

Lets the Pi coding agent drive real Linux desktop apps on Omarchy (Hyprland Wayland) by reading the accessibility tree and asking Jev for the target element and the operation. It offers 11 Wayland-safe element operations. Jev-driven actions abstain below 0.55 confidence and need confirmation below 0.70, or 0.90 for destructive ones; direct operations on a known element run without Jev.

Paul-Yuchao-Dong · ★ 0 · MIT · Jev

  • computer-use
  • linux
  • agent

Decision Wall: 200 questions about one text

Source: charles-forsyth/jev-decision-wall ↗

Asks Jev 200 yes/no questions about one text in a single call and shows the answers as a heatmap. The keyless hosted demo replays recorded answers. VENDOR-REPORTED: about 185 ms for one question, 200 ms for 50, and 150 to 300 ms for 200; seven parallel calls returned 1,400 answers in 282 ms, against 1,092 ms back to back. The author measured Jev 1.14 from a US home connection and has not measured calibration.

charles-forsyth · ★ 0 · MIT · Jev

  • classification
  • heatmap

Jev-Router: choose a model after applying hard constraints

Source: AIAnytime/Jev-Router ↗

An OpenAI-compatible router that filters models by hard constraints before Jev judges which one fits. VENDOR-REPORTED, on its own 30 prompts: tier accuracy was 100% against 53.3% for a heuristic, task-type accuracy 83.3% against 46.7%, and hard prompts sent to a weak model 0 against 14. Estimated savings against always using the strongest model, from token counts and configured prices rather than running the chosen models, were 35.6% against 68.7%; the heuristic's estimate was higher because it under-routed. Decision latency was 295 ms at p50 and 409 ms at p95.

AIAnytime · ★ 0 · MIT · Jev

  • routing
  • agent

PR wall: separate judgments about each pull request

Source: House-elves/pr-wall ↗

Puts open pull requests on a wall and asks Jev eight typed questions about each diff and its tests, using quarkusio/quarkus by default. It keeps the answers separate and never combines them into a score. Right/Wrong feedback records corrections and groups accuracy by confidence as you label answers; no accuracy figures are published yet. Its questions and Quarkus context are adapted from brunobat/quarkus-pr-wall.

House-elves · ★ 0 · Apache-2.0 · Jev

  • code-review
  • calibration

OwnYourTimeline: filter the X Home feed

Source: raghavio/ownyourtimeline ↗

Filters the For you and Following feeds in Chrome or Edge using a plain-language instruction and Jev. It sends one bulk TypeSafe request per timeline response, splitting to stay within input budgets, and removes posts scoring at least 0.90 before X renders them. Errors and timeouts leave posts visible; it checks at most 80 posts per response. The built extension has Chromium tests with X and TypeSafe responses stubbed. No filtering-accuracy figures are published.

Raghav Sharma · ★ 0 · MIT · Jev

  • feed-filtering
  • browser-extension

Jev router for GitHub Copilot

Source: TechPreacher/jev-router-copilot ↗

Jev sizes a Copilot message as tiny, everyday, large or hardest and sends it to a helper agent pinned to a model. Defaults are Haiku 5.5, Sonnet 5.5 and Opus 5.5, with the hardest helper configured to request high effort. Recorded helper runs used medium effort. The author records live runs of the hook in Copilot CLI 1.0.105 and VS Code 1.144, plus the CLI wrapper. The MCP fallback is tested offline only. Its 54 offline tests passed when checked on 03 Nov 2026; it publishes no savings benchmark.

Sascha Corti (TechPreacher) · ★ 0 · MIT · Jev

  • model-routing
  • coding-assistant

Source: Live CLI wrapper run → Source: Live VS Code run →

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