A fast scanner that reviews code for correctness, security, reliability, compatibility and test gaps, with actionable feedback. Supports the Jev API and local models.
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A fast scanner that reviews code for correctness, security, reliability, compatibility and test gaps, with actionable feedback. Supports the Jev API and local models.
GitHubTriage & routing
Jev triages streaming logs into page, digest or resolve, cutting alert noise and paging humans only for high-confidence incidents. About $1–3 for 1M events a month.
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npm install is the scariest command in your terminal. One typo → lookalike package → malicious postinstall → secrets gone. jev-sec-audit flags it in milliseconds using Jev, a System 1 model built for fast decisions, not chat. One step in GitHub Actions. Open source.

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Sitequiet
Sponsored
Uptime monitoring, status pages and client reports for agencies.

A local Codex router asks Jev to choose the next model and reasoning effort while forwarding the complete conversation to that model.
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Jev selects search sources and time ranges, then scores result relevance in a multi-engine search app with editable filters.
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Jev-powered Agent #Jev Built a local resume screening workbench for HR teams and early-stage founders. You define the bar → upload resumes in bulk → it checks every condition → every verdict has a quote from the resume to back it up. Not "AI thinks it's a fit." More like:
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Built a deal-review demo around Jev. It recommends what comes next: approval, more documents, or sales, finance and legal review. One deal can need several teams. Jev maps that out; people still make the call. #Jev #EnterPro #EnterArtifact
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Built a scam sms detector using jev https://t.co/dH47rRWM85 Copy-paste the sms and it gives you probability if the sms is a scam or not. :)
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not every task needs the same model built Auto Jev-Codex for Paseo to pick the right setup for each turn open source

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My time with a US-based remote startup recently came to an end. So I made every YC company interview my resume. Jev read it against all 6,245 YC companies in 25 seconds. Cost: $0.37. 156 founders should take my call. The list, the workflow, and the tool 🧵

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hopping on the jev bandwagon. built a tiny project to declutter my internet life: TabJev 🗂️ Open a tab → it figures out if it’s Work, Dev, Social, etc. → puts it in the right group. Use the defaults or create your own groups. Free. Open source. Bring your own key.

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I keep defaulting to the strongest model and highest effort just to play it safe. So I made Switchboard to choose for me in Codex and Claude Code. It’s open source and powered by @typesafeai Jev (but support for other System One models coming soon). Give it a try and tell me
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Jev doesn’t write code. I use it to decide which model should. I built Jevonian, an open-source local router for coding agents. Keep your agent. Jev picks the model and thinking effort for each turn. See what ran, why it was picked, and its estimated cost. Built with

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I built Inbox triage using Jev 🤯 So I point my gmail to jev and it classifies all the emails i have in my inbox and put them in specific category folder. It was built using claude. I also published a small demo video on my youtube. Sharing the repo and youtube link below.
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Open-source router where Jev picks local Qwen or hosted Sonnet per request, with a UI showing each routing decision.
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aeogeolabs
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Get recommended in ChatGPT, Perplexity and Google AI Overviews.

A public demo asks Jev 18 typed questions about a deployment, including tests, rollback and availability, then converts the probabilities into an inspectable verdict.
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Classifies each outbound agent email with Jev before it reaches Resend, blocking abusive bulk outreach at the API boundary.
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A client workflow uses Jev to label emails by priority and other signals; the author says a demo is live on their site.
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Built content-aware PII redaction in Postgres with @neondatabase and @typesafeai's Jev where redaction on support messages is not on entire column bluntly, but only on meaningful bits: https://t.co/sOSG4tXCot 🎉 • Jev reads each message and tags the personal bits: names,
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JEV is INSANE. 4,000+ people applied for internship at @tryAlanAI. So we built an in house review console to find evidence of real work at scale. Every square is a real SDE intern application > 3,518 applications checked in 4:54 > 20 surfaced for human review > Estimated Jev
### Jev only answers yes/no or pick-one. 16,000 calls: against gpt-5.4-mini and gpt-5.6-luna on four public datasets, then on a few thousand real pipeline decisions. Where it…
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Jev was the tipping point - I built the last MySQL search statement - WPS ... # Jev was the tipping point - I built the last MySQL search statement ... So I built AILIKE. It lets…
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What we're really tackling is this: How can AI truly assess a resume without falling into the trap of just echoing buzzwords? How do we know the candidate isn't just sprinkling…
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Geopolitical dashboard that batches Jev 1.13.0 headline-severity and topic classifications, validates the answers, and falls back when classification fails.
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Classifies text-bearing PDF pages into IRS form and page-kind candidates with a confidence gate; document triage, not tax advice, and scanned pages need OCR.
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Omi
Sponsored
Gentle daily affirmations on your Home Screen and Lock Screen.

Navigates a Neo4j graph by having Jev score neighbouring relationships, then beam-searching for the most probable path.
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LlamaIndex reranker and selector using Jev Score and Choice answers, with configurable confidence handling.
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SQL-like filtering, ranking, classification, and scoring with natural-language predicates.
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Read-only Gmail triage that stores messages locally and asks Jev for bounded category, urgency, and human-sender probabilities.
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Fetches a public SaaS page as Markdown, then asks Jev ten bounded questions about likely first-visit comprehension; URL validation, caching, sanitization, and presentation remain…
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Email assistant where Jev is an optional classifier backend returning bounded categories and yes/no probabilities.
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Yeah Jev by @typesafeai is very cool. It classified 500 emails in seconds. And it costed 3.5 cents.
this model is actually insane at email classification i tested it on 1500 of my own emails to see how well it works and I am blown away
Sitequiet
Sponsored
Uptime monitoring, status pages and client reports for agencies.

Jev + Kimi K3 for fraud detection! TLDR: Jev classified 100 emails in 1.42 seconds, then I routed the uncertain cases to Kimi K3. The full pipeline got 96/100 correct for only ~$0.07. Video is not sped up, check out the live run! Here was my process: I gave Jev 100 emails to
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