The full directory
All Jev AI model resources
Entries for TypeSafe AI's flagship System One model — official docs and SDKs alongside community clients, tools, and write-ups.
- Entries
- 3,904
- Categories
- 11
- Official
- 102
- Community
- 3,802
- Source sites
- 293
- Deep dives
- 3,904
By format
3904- Docs169
- Repos & sites3095
- Videos74
- Posts104
- Articles384
- Playgrounds78
Updated
Browse the Jev AI model by category
11 ways into the ecosystem. Each category page leads with its own shortlist of starting points.
Browse the Jev AI model by use case or industry
The same directory, sliced by what you are building and who you are building it for.
All 3904 Jev AI model resources
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Showing 3361–3408 of 3904 resources
nokia-applied-research/AnyJevPythonStart here with the Jev AI model
Hand-picked entries the maintainers recommend first, from official primitives to community tools.
Newest Jev AI model resources
The latest additions to the directory, newest first.
Can Jev Improve Demonstration Retrieval for In-Context Learning?Jev Benchmarks & Evaluations
Don't Call It a Decision ModelJev Practices & Patterns
Fast, Cheap, and Fair? Evaluating Decision ModelsJev Benchmarks & Evaluations
JEV-27B for Core AIJev Models & Reimplementations
JevBreak: Your Model, Their DecisionJev Benchmarks & Evaluations
- LLM Output Evaluation with ClefJev Benchmarks & Evaluations
From the Jev community
Watch walkthroughs, read the threads, and see what builders are posting.
YouTube: KodeKloud's three-minute primer: what a System One model decides, and why it answers in milliseconds.
YouTube: Caleb Writes Code explains what Jev is and how to call it, in seven minutes.
YouTube: Greg Isenberg and Ryan Vogel on the businesses Jev unlocks, and a path in through the Vercel AI Gateway.
YouTube: CJ from Syntax demos browser use, classification, code review, a model router, and a chat bot with no LLM.
YouTube: Ryan Vogel runs Jev on 100 and then 1,000 emails: category, priority, spam, and reply predictions.
YouTube: AICodeKing tests support routing, refund detection, prompt-injection resistance, and browser automation.
Hacker News: Show HN: Ad Spend Guard gates budget before the auction, not the creative after.
Show HN: Gating ad budget with a decision modelRead the thread on Hacker NewsReddit: Reranking rebooking options with a decision model, ranked with reasons.
Hacker News: Pick Verify: a single decision at the warehouse pick station catches confusable picks.
Show HN: Verifying robot picks with a decision modelRead the thread on Hacker NewsHacker News: Decision Index 0.2.1 scores open reproductions of Jev on a frozen suite.
jackbravo4 pointsDecision Index 0.2.1 – 70 open reproductions of TypeSafe Jev's Decision ModelRead the thread on Hacker NewsHacker News: Software Bombe and live Enigma demo where Jev ranks cribs and judges plaintext.
ag_212 pointsShow HN: Jev as the Bletchley Park Analyst: A Software Bombe on EnigmaRead the thread on Hacker NewsHacker News: Show HN for the decide CLI: brew install, file context, and multi-question shell scripts.
vsekhar2 pointsShow HN: Decide – Jev decisions in the shell, scripts, and agent skillsRead the thread on Hacker NewsHow entries are chosen
Every entry is reviewed against the same bar, whether it comes from TypeSafe or the community.
- Public and working — no paywalls, sign-up walls, or dead links.
- Concrete — it has to be about Jev and the System One API, not generic LLM content.
- Useful today — something a developer can learn from or use right now.
- Distinct — if a similar entry exists, the description has to say what makes this one different: a different runtime, a cheaper path, a measured result, or a narrower focus.
- Documented — repos state their license, and docs are in English or carry an English summary.
Spam, affiliate links, and thin AI-generated content are rejected. New entries are expected to ship with a deep dive: two to five highlights, caveats, a quickstart snippet where one helps, and a verification date. Star counts are refreshed when an entry is touched.
Common questions
Short answers about Jev and how this directory works.
What is the Jev AI model?
Jev is TypeSafe AI's first System One model — an AI model that takes a state plus typed questions and returns one structured answer per question: a choice, an ordered score, or the probability of yes, with calibrated confidence on Choice and Score answers. Code can branch on the result without parsing generated text.
What is the difference between Choice, Score, and Noul?
They are the three question primitives. Choice picks one of up to 255 options, Score rates on 2 to 10 ordered levels, and Noul answers yes or no. Choice and Score answers carry a confidence between 0 and 1; a Noul answer is the probability of yes.
Which Jev SDKs and client libraries are available?
TypeSafe maintains official JavaScript/TypeScript and Python SDKs plus a Python adapter. The community has built clients for Go, .NET, PHP, Laravel, Rust, Elixir, Ruby, and Scala, along with framework integrations such as DSPy, LlamaIndex, and Home Assistant. All of them are listed in the Repos & SDKs category.
Is the directory free, and is it affiliated with TypeSafe AI?
The directory is free to browse: every entry is reviewed, and spam, affiliate links, and sign-up walls are rejected. JevDirectory.org is community-run and not affiliated with TypeSafe AI — Jev and System One are TypeSafe AI trademarks.
How often is the directory updated?
Entries are added as new resources appear and re-checked when they are touched. The directory currently holds 3904 entries from 293 source sites, last updated Nov 5, 2026.
What is a verified deep dive?
Most entries include a deep dive: two to five highlight bullets someone would only know from using the resource, a caveats note about limits and requirements, an optional quickstart snippet, and the date the link was last checked. 3904 of the 3904 entries carry one today.
For the canonical details, read the official TypeSafe docs and the API reference.