TypeSafe AIAI Model API
Jev
Jev reads text or structured state and answers typed Choice, Score, and Noul questions with probabilities and confidence. It is served through TypeSafe's System One API for routing, guardrails, extraction, and other software decisions.
The 30-Second Take
Pick Jev for the repeated decisions your software makes where a fixed set of answers settles the call.
TypeSafe's typed API takes state and a question and returns a choice, a score or a yes/no with probabilities. Serverpod and MotherDuck run it in production for routing, document choice and reranking.
- Best fit
- Teams with repeated decisions that currently parse model prose or call a larger language model for every branch.
- Main constraint
- Each workload needs its own evaluation: trained classifiers beat it on stable labels at Cisco and Anaconda, it found none of 13 code-review problems at Brief, and hostile page text can steer it.
- First move
- Write a small decision set, run Jev beside the current path, and measure accuracy, latency, and review rate.
Why
Watch where it loses: trained classifiers beat it on stable labels at two companies, and it found none of 13 code-review problems in one test. Each workload needs its own evaluation, with a fallback.
Practitioner sentiment, teams and leaders+40 Positive
25 practitioners, 139 sources reviewed, Updated Oct 30, 2026How this is measured
Read the GILD Review
Save a product your organization uses.Keep up with Jev without adding it to your stack.Visit Website
- Operating stack
- AI Application Platform
Models
Which models does Jev serve, and where is each strong?
Each model's page charts its public benchmark scores beside any other model you layer on it.
Comparisons
How does Jev compare with the alternatives?
Jev vs Claude API
- AI Model APIs
Jev returns typed decisions with probabilities and confidence for narrow software branches. Claude is a general language model API for generation, reasoning, and tool use. Compare the decision contract, fallback path, and cost on the same workload.
Jev vs OpenAI API
- AI Model APIs
Jev is built around structured decisions and parallel questions. The OpenAI API spans generation, reasoning, tools, and structured outputs. The right choice depends on whether the workload needs a narrow decision contract or a broad model surface.
Operator Insights
What are teams learning from building on Jev and running it in production?
Ben BartholomewHindsight teamVectorize
Hindsight, Vectorize's open-source memory server for agents, release 0.10.1.
Hindsight blog (Vectorize), published Read the write-up (opens Hindsight blog (Vectorize) in a new tab)
Observation
Vectorize shipped Jev as Hindsight's reranker at recall@1 of 0.950 against 0.800, and left its pruning off because it cut 19% of the evidence.
- Takeaway
- Use Jev's ranking and keep pruning off until you have measured what it drops.
- What happened
- Every Hindsight deployment can now run Jev as an opt-in reranker. On LoCoMo with 30 candidates, the team measured recall@1 of 0.950 for Jev against 0.800 for its default local MiniLM reranker, at 0.027 against 0.12 seconds per query (Sep 24, 2026). Optional pruning cut 19% of the gold evidence, so it ships off.
“It also cuts 19% of the gold evidence. On a real bank it took 300 candidates down to 3. We went back and forth on the default and landed on off.”
Ben Bartholomew - Public engineering write-up
- Measured results reported
Deployment details
Hindsight, Vectorize's open-source memory server for agents, release 0.10.1.
- Public engineering write-up
- Measured results reported
- Team
- Hindsight core team at Vectorize
- Workload
- Reranking memories at recall time
- Product version
- Hindsight 0.10.1 with Jev
- Model
- Jev against a local MiniLM reranker
- Measurement
- Recall@1 0.950 against 0.800 at 0.027 against 0.12 seconds per query (Sep 24, 2026)
srnsnemilkapa.ai team, posting its benchmarkkapa.ai
kapa.ai, which runs millions of retrieval queries a month over its customers' docs, Slack threads, tickets and code.
Reddit, r/LLMDevs, published Read the write-up (opens Reddit, r/LLMDevs in a new tab)
Observation
kapa.ai found Jev 1.14 within 0.003 of the best reranker on 1,000 production-style cases, and chose Voyage instead because Voyage was also cheaper and faster.
- Takeaway
- Benchmark a reranker on your own queries: Jev nearly tied the leader on quality and still lost the decision on cost and speed.
- What happened
- kapa.ai reranked the top 50 hybrid-search chunks for 1,000 cases from its Company Knowledge Bench with Voyage, Cohere, Qwen and Jev. Jev 1.14 scored 0.532 against 0.535 for Voyage rerank-3, and beat Cohere rerank-v4.0-pro on score, cost (US$2.49 against US$3.42 per 1,000 questions) and median latency (0.28 against 0.77 seconds). Voyage rerank-3 also cost the least at US$1.91 and ran fastest at 0.18 seconds, so kapa.ai chose Voyage instead and is staying with it (Reddit, Oct 20, 2026).
- Public organization write-up (Reddit post)
- Measured results reported
Deployment details
kapa.ai, which runs millions of retrieval queries a month over its customers' docs, Slack threads, tickets and code.
- Public organization write-up (Reddit post)
- Measured results reported
- Team
- kapa.ai
- Workload
- Reranking 50 retrieved chunks for 1,000 Company Knowledge Bench cases
- Product version
- Jev 1.13 and Jev 1.14, binary and graded questions
- Model
- Voyage rerank-3 and rerank-2.5, Cohere rerank-v3.5 and v4.0, Qwen3 reranker 8B
- Measurement
- Retrieval score 0.532 for Jev 1.14 against 0.535 for Voyage rerank-3 (Oct 20, 2026)
Buying and deployment
What a team building on it should verify before production traffic grows.
Sourced from TypeSafe documentation
Signals
What is the current evidence saying about Jev?
What teams and developers report from running Jev, from production defaults at Isotopes AI and Serverpod to kapa.ai's choice of Voyage, across Reddit, GitHub, engineering blogs, X, Hacker News, podcasts and videos, with every finding linked to its sources.
Practitioner sentiment, teams and leaders
+40 Positive net
of 25 sources that take a side, each author counted once. Small sample.
How this figure is madeCurrent sentiment
Positive, mixed and negative sources
12112
Teams report production use and clear losses. Isotopes AI keeps Jev 1.13 as its default after it passed 100% across three runs of 88 scenarios, Serverpod roughly halved its assistant's time to first token, and Deel reports up to 59 times lower cost. kapa.ai chose Voyage after Jev came within 0.003 on reranking, Cisco and Anaconda beat it with trained classifiers, and dessn moved more than 10,000 Jev calls to one Claude Opus 5.5 call for accuracy.
Run a pilot on your own prompts to measure output quality and cost per task.
Evidence field. All 139 sources, one mark each.
Arrange by
Each mark is one source: positive, mixed, negative, no opinion stated, or documentation (not counted).
| Group | Sources | Positive | Mixed | Negative | No opinion stated and not counted in the score | Documentation, checked and not counted |
|---|---|---|---|---|---|---|
| Positive | 12 | 12 | 0 | 0 | 0 | 0 |
| Mixed | 11 | 0 | 11 | 0 | 0 | 0 |
| Negative | 2 | 0 | 0 | 2 | 0 | 0 |
| Not counted | 17 | 0 | 0 | 0 | 17 | 0 |
| Documentation | 10 | 0 | 0 | 0 | 0 | 10 |
| Outside this group | 87 | 8 | 7 | 2 | 70 | 0 |
| Quarter | Sources |
|---|---|
| Q3 2026 | 47 |
| Q4 2026 | 82 |
| Documentation, checked | 10 |
By sentiment
10 documentation pages check facts and are not counted; 87 sit outside this group.
Hover a mark for a quick look, click it or press Enter to open its source.Tap a mark to open its source, then step to its neighbors with Previous and Next.
What practitioners praise
Top praise of 4. Each mark is a source on it; filled marks praise it.
Most common concerns
Top concern of 3. Each mark is a source on it; filled marks raise it.
All 139 sources behind these findings
- Neurotype experiments scored by JevKyle Wild, builder of poor-things.com (self-described: A few million steering experiments on Qwen3.5-4B, each output evaluated by Jev and Fireworks Rune), X post, published Oct 27, 2026
- Comment on: Ask HN: Who is hiring? (October 2026)TypeSafe AI (Vendor recruiting notice on Hacker News), Hacker News recruiting notice, checked Oct 26, 2026
- Tested decision models (Jev, Kev, Clef, OpenAI Decisions): the confidence score really worksCardiologistOk2154, publisher of the jev-on-durians repository (self-described: Comment categorization across four decision models, with code and data on GitHub), Reddit post, r/LLMDevs, published Oct 26, 2026
- Comment on: open decision modelstheanonymousone, Hacker News commenter (self-described: A first Jev use case, compared informally with models on OpenRouter), Hacker News comment, published Oct 26, 2026
- TypeSafe AI releases Jev, a new System One modelTypeSafe AI (Public launch announcement on X), X post (founder announcement), checked Oct 26, 2026
- TypeSafe IntroductionTypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe ModelsTypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe System One APITypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe ConfidenceTypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe Intent RoutingTypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe Jev jaggednessTypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe Jev launchTypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- TypeSafe Jev 1.14TypeSafe AI (Official documentation), Product documentation, checked Oct 25, 2026
- decide(): no way to enable Jev long-context mode (TypeSafe-Danger-Zone-Long-Context header)Matt Apperson, maintainer of noetic (self-described: Spec-to-code completeness workflow sending about 51k input tokens per decision), GitHub issue, mattapperson/noetic, published Oct 25, 2026
- Comment on: classifiers and decision modelsmagicalhippo, Hacker News commenter (self-described: Sorting customer product descriptions into government categories that change several times a year), Hacker News comment, published Oct 25, 2026
- Comment on: classifiers and decision modelsnico, Hacker News commenter and creator of the Jeffy classifiers (self-described: A classification benchmark across label counts), Hacker News comment, published Oct 25, 2026
- Jev for image classification on an art datasetAlexandru Indrei, Principal Engineer at Amazon, posting his own test (self-described: Image classification on an art dataset), X post, published Oct 24, 2026
- Weekend tests of Jev against ClefJeremy Morrell, principal engineer, Cloudflare Observability (self-described: Weekend use-case tests comparing Jev and Clef), X post, published Oct 24, 2026
- Comment on: The rise and fall of Jev hypeleemoore, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 23, 2026
- Remove the Jev (TypeSafe) injection classifier; keep the regex scanfuad-daoud, maintainer of relevo (self-described: relevo's optional prompt-injection classifier), GitHub issue, published Oct 23, 2026
- Comment on: Using LLM for confidence scoring is a bad idearahimnathwani, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 22, 2026
- Jev inside the Lightpanda browserLightpanda, maker of a browser built for machines (self-described: A judge() call built on Jev inside the Lightpanda binary), X post, published Oct 21, 2026
- [Harness]: Jevernoaapa, maintainer of a kagent harness for Jev (self-described: A kagent harness that runs Jev as a judge agent, tested in the author's own cluster), GitHub issue, published Oct 21, 2026
- Decision Models: Jev vs. a Fine-Tuned ClassifierPhilipp Rudiger, Anaconda (self-described: Anaconda's comparison of Jev, a fine-tuned Qwen3 0.6B model, and XGBoost on 2,400 held-out CFPB complaints), Engineering blog post, Anaconda, published Oct 20, 2026
- We tested Jev as a reranker against Voyage, Cohere and Qwen on 1,000 eval casessrnsnemil, posting kapa.ai's benchmark (self-described: kapa.ai's Company Knowledge Bench, 1,000 cases built from real production queries), Reddit post, r/LLMDevs, published Oct 20, 2026
- How to Build a Decision Model Like JevJeremy Greer and Matthew Persons, Oumi (self-described: Oumi tests of Jev 1.13 on rare-fact questions and documents from short to very long), Engineering blog post, Oumi, published Oct 19, 2026
- Comment on: content moderationr1n-ai, builder of an adult-content product (self-described: Moderation for an adult-content product, tested on OpenAI's published moderation test set), Reddit comment, r/LLMDevs, published Oct 18, 2026
- TypeSafe reranker can exceed Jev context within the local token budgetpedropaulovc, developer running Hindsight's TypeSafe reranker in production (self-described: Hindsight memory recall with a Jev reranker), GitHub issue, vectorize-io/hindsight, published Oct 17, 2026
- Replacing a FastText and Gemini pipeline with one Jev callArpit Tripathi, builder of MemX, ex-Google and ex-AWS (self-described: MemX app classification pipeline), X post, published Oct 17, 2026
- Jev Router Experiment with OSS models for Coding TasksShivay Lamba, developer who published the benchmark (self-described: 50 coding tasks routed by Jev across DeepSeek V4 Flash, Kimi K2.6 and Kimi K3), Independent benchmark, GitHub repository, published Oct 16, 2026
- Comment on: email-reply classificationianreboot, developer of an email-reply classifier (self-described: An email-reply classifier with about 14 categories, 51 cases run three times), Reddit comment, r/LLMDevs, published Oct 16, 2026
- Comment on: We're releasing Jev 1.14.0 along with experimental features for dreamersbbor, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 15, 2026
- Comment on: We're releasing Jev 1.14.0 along with experimental features for dreamerseinsteinx2, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 15, 2026
- Comment on: Jev meets the Trolley Problemzlandes86, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 15, 2026
- Comment on: Jev meets the Trolley Problemcziou, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 15, 2026
- Beyond the leaderboard: decision models in a real workflowPrasanth Jayachandran, author of Isotopes AI's engineering write-up (self-described: Isotopes AI aidnn follow-up workflow, 88 scenarios run three times per model), Engineering blog post, Isotopes AI blog, published Oct 15, 2026
- 0.7.0 fails every request on Bun with "TypeError: Body already used" (bufferResponse)dinhphieu, developer using the TypeSafe JavaScript SDK (self-described: TypeSafe JavaScript SDK 0.7.0 on Bun 1.4.3 and Node 26), GitHub issue, typesafe-ai/typesafe-sdk-js, published Oct 15, 2026
- Evaluate and upgrade the Jev judge to jev-1.14.0ibuildthecloud, discobox maintainer (self-described: discobox judge pinned to jev-1.13.0 with tuned thresholds), GitHub issue, discobox-ai/discobox, published Oct 15, 2026
- Jev decisions on photos with the box typeCarlneil, AI engineer at Clouted (self-described: Image decisions with Jev 1.14 and the box type), X post, published Oct 15, 2026
- Comment on: We're releasing Jev 1.14.0 along with experimental features for dreamersgopalv, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 14, 2026
- Jev Talking: Security Concerns for Models That Return Decisions Instead of TextKevin Kelleher, HiddenLayer, reporting HiddenLayer Research's tests (self-described: HiddenLayer Research tests of a Jev browser agent on a simulated checkout and of Jev as a toxic-prompt filter), Engineering blog post, HiddenLayer, published Oct 14, 2026
- Building a Fact-Extraction Pipeline w/ JevHonest_Medium_2872, newsletter author (self-described: A newsletter's pipeline for infographic cards drawn from long posts), Reddit post, r/LLMDevs, published Oct 14, 2026
- Jev handed our LLM the wrong page a tenth as often as our embeddingsSayora, AI phone-receptionist developer (self-described: Retrieval evaluation described in the linked engineering post), Engineering blog post, Sayora, published Oct 13, 2026
- Our RAG kept retrieving the wrong page, so we tested letting Jev pick pages insteadjacobsayora, developer building an AI phone receptionist (self-described: Four-site retrieval test with 168 questions), Reddit post, r/Rag, published Oct 13, 2026
- Using Jev to make your agents write the code and design the app the way you doAtul, developer and author of the a7ul engineering blog (self-described: Agent rule checks and screenshot review), Personal engineering blog post, a7ul.com, published Oct 12, 2026
- Comment on: Build your own decision modele12e, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 12, 2026
- Comment on: Build your own decision modeljrmg, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 12, 2026
- Comment on: Build your own decision modeluser43928, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 11, 2026
- Comment on: Build your own decision modelsoftwaredoug, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 11, 2026
- Task classifier with Jev - pretty good experience so far!Dependent-Dinner-918, creator of the Keen Code open source coding agent (self-described: Keen Code task routing), Reddit post, r/JevAI, published Oct 11, 2026
- We started using JEV to clarify queries before retrieval, and the results have been pretty interestingCraft_Show, developer building an enterprise AI knowledge-management application (self-described: Enterprise retrieval and answer generation workflow), Reddit post, r/Rag, published Oct 11, 2026
- Comment on: routing questions to the right keypWiklacz, developer of a question router (self-described: 650 Polish messages with a known correct key, Jev against a Perplexity router and local Von), Reddit comment, r/LLMDevs, published Oct 11, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bcootsnuck, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bincompressible, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bxxmarkuski, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5B999900000999, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bdannyw, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5B-HIMAO-, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5Br4indeer, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 10, 2026
- Comment on: OpenAI's decision modelrockwotj, Hacker News commenter (self-described: Production use cases the commenter runs on Jev), Hacker News comment, published Oct 10, 2026
- I tested dynamic model routing for an agentic browser-testing system. Guardrails via Jev worked pretty good.shane-testronaut, builder of Testronaut (self-described: Testronaut, an agentic browser-testing system, over 120 isolated mission runs), Reddit post, r/LLMDevs, published Oct 10, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bjypepin, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bnlpnerd, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bgeoffschmidt, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bambicapter, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bbushbaba, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5BTeMPOraL, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Microsoft-Decision-1, our model for fast decision-makingsass1caia, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bcheesecakegood, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Typesafe AI raises $870M at $7.5Bcharm137, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- Comment on: Microsoft-Decision-1, our model for fast decision-makingelzbardico, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 9, 2026
- I got Jev to zero mistakes. I'm still using Flash-Lite.Mike Swift, CEO and co-founder of Major League Hacking (self-described: MLH routing evaluation across thousands of runs), Developer blog post, DEV Community, published Oct 8, 2026
- I built a Claude Code plugin that uses Jev for compaction, model routing and skill selectionFit-Fail-3369, builder of the optim-jev plugin (self-described: optim-jev, a Claude Code plugin for context compaction, model routing and skill choice), Reddit post, r/LLMDevs, published Oct 8, 2026
- Telling my agent to delegate its browser clicks didn't work; hiding its own click and type tools didHrishikesh90, builder of a browser-click tool (self-described: A tool that hands an agent's browser clicks to Jev, benchmarked against Claude Sonnet 5.5 clicking on its own), Reddit post, r/AI_Agents, published Oct 8, 2026
- Comment on: Decisions API is in public betaehe78qhe, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 7, 2026
- Comment on: action-set size in agent gatesCtbhatia, developer running Jev gates in production (self-described: Jev gates on agent actions, run all day), Reddit comment, r/LLMDevs, published Oct 7, 2026
- Comment on: [dead]upguardnews, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 6, 2026
- Comment on: Decisions API is in public betatmhall, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 6, 2026
- Comment on: Decision models like Jev don't beat LLM-as-a-judge or traditional classifiersGarlef, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 5, 2026
- Comment on: Decision models like Jev don't beat LLM-as-a-judge or traditional classifierskwinkunks, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 5, 2026
- Jev: Decision Models on TrialPrashanth Arun, Director of Data Science, AI Defense at Cisco, with Jin Ma (Cisco AI Defense content-safety evaluation on six datasets and eight public benchmarks), Engineering blog post, Cisco Blogs, published Oct 5, 2026
- Comment on: prompt-injection checkspWiklacz, developer testing Jev for prompt-injection checks (self-described: Two weeks of prompt-injection checks with a yes/no question), Reddit comment, r/LLMDevs, published Oct 5, 2026
- Jev Isn't an LLM: I Tried TypeSafe AI's Decision Model in GoEd Zynda, host of What The Func? (self-described: Hands-on Go examples of yes/no decisions, routing choices and frustration scoring), Video, YouTube (What The Func?), published Oct 5, 2026
- Hidden Risks of Jev: An Empirical Study of Security, Privacy, and Dual UseShang Wang, Tianqing Zhu and coauthors, research paper authors (self-described: Security and privacy attacks on the Jev API and a local stand-in model), Independent benchmark, arXiv, published Oct 4, 2026
- Comment on: jev-pagesdorongrinstein, Hacker News commenter (self-described: Deploying the open jev-pages example with a TypeSafe API key), Hacker News comment, published Oct 4, 2026
- Daily usage endpoint that works with an API key?mlahargou, engineer on iFixit's FixBot (self-described: iFixit FixBot, about 8,869 Jev requests on one day), GitHub issue, typesafe-ai/typesafe-sdk-python, published Oct 2, 2026
- Comment on: choosing a decision architecturemagicdoorai, contributor to magicdoor.ai, which routes with Jev (self-described: magicdoor.ai's request routing), Reddit comment, r/LLMDevs, published Oct 2, 2026
- Comment on: Gemini 4 ArgonParacompact, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 1, 2026
- Comment on: Is sandboxing sufficient to contain rogue agents?simonw, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 1, 2026
- Comment on: Clef: Open-weight decision models, and new RL fine-tuning platformamluto, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Oct 1, 2026
- Feature request: Jev / TypeSafe AI support in @posthog/aijuanmarin-co, developer running Jev beside Gemini (self-described: An application that calls Jev through TypeSafe's SDK alongside Gemini), GitHub issue, published Oct 1, 2026
- Comment on: Clef Flashralusek, Hacker News commenter (self-described: A latency test of Jev through TypeSafe and OpenRouter against Clef Flash), Hacker News comment, published Oct 1, 2026
- Comment on: ChimpBench - Chimpanzee Population Simulatorjbermudez5, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Sep 30, 2026
- Building a harness with JevLangChain engineering team (self-described: Engineering harness built around Jev), Engineering blog post, LangChain, published Sep 30, 2026
- Updated my memory system to use jev as a reranker 97% on LongMemEvalturlockmike, builder of the deep-recall memory system (self-described: deep-recall, an open-source agent memory system on hybrid vector search and graph search), Reddit post, r/Rag, published Sep 30, 2026
- Comment on: where decision models fitgodwin-pinto, who runs the Encatch feedback platform (self-described: Encatch, a feedback platform with Jev live as an optional production feature), Reddit comment, r/LLMDevs, published Sep 30, 2026
- Comment on: Show HN: Jevpipe - a fast System 1 for AI agents, as a Unix pipecs1996, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Sep 28, 2026
- Comment on: Jeff - Jev-compatible 0.8B decision models, trained at home, ~30 msfirelex, Hacker News commenter (self-described: Public discussion of Jev or System One models), Hacker News comment, published Sep 28, 2026
- Jev guardrails in production: a security platform's front door for five cents a day.Alexander Myasoedov, Founder, Metaheuristic (Metaheuristic's intent and report-quality gates for a cybersecurity client, on jev-1.13 through OpenRouter), Engineering blog post, Metaheuristic, published Sep 28, 2026
- Show HN: jevpipe, a command-line wrapper for Jevbothlabs, builder of jevpipe (self-described: jevpipe, an open-source command-line tool that lets agents filter and label data with Jev), Hacker News comment, published Sep 28, 2026
- Comment on: Pouring a year of RAG experience into my AI document spreadsheet appNo-Afternoon-4057, developer running a hybrid retrieval stack (self-described: Jev as a reranker after hybrid search with reciprocal rank fusion), Reddit comment, r/Rag, published Sep 28, 2026
- Jev vs. Claude vs. GPT: Your "Critical" Findings Are Stealing Your SprintEleanor Sigel, author of Casco's benchmark (self-described: 2,449 security findings scored for CVSS 3.1 by eight models against Casco's published scores), Engineering blog post, Casco, published Sep 28, 2026
- TypeSafe Jev guide and practical use casesHarsh, Composio (self-described: A Jev toolkit in Composio's Tool Router), Blog post, Composio, published Sep 28, 2026
- Jev for beginners: how to use it and what to buildClaire Vo, host of How I AI, showing her ChatPRD projects (self-described: Five of the host's own projects run on Jev, including ChatPRD's product-insights graph), Podcast episode, How I AI, published Sep 28, 2026
- Supported pre-dispatch context admission and billing reconciliation for pinned Jevdiannt, developer integrating Jev's HTTP API with budget reservations (self-described: Direct HTTP API integration with pinned jev-1.13.0 requests), GitHub issue, typesafe-ai/typesafe-sdk-js, published Sep 27, 2026
- Racing Spinny's production ticket routing against JevSanchit, software engineer on Spinny's Customer Experience team (self-described: Spinny ticket categorization and urgency detection built on OpenAI), X post, published Sep 27, 2026
- I built a LinkedIn AI slop detector using JEVgoodvibezone, builder of a Chrome extension (self-described: A local Chrome extension that rates LinkedIn posts with Jev checks and rules), Reddit post, r/LLMDevs, published Sep 27, 2026
- Comment on: judging stories with Jevrcastag, developer judging stories with an agent (self-described: Jev as a judge of written stories, compared with Claude), Reddit comment, r/PromptEngineering, published Sep 26, 2026
- Choice answers:
choiceis sometimes 0.01 below the highest probability (jev-1.13.0)nevenincs, developer running a production Jev integration (self-described: Production integration asking 28 questions per request), GitHub issue, typesafe-ai/typesafe-sdk-python, published Sep 25, 2026 - Deel put Jev head-to-head with frontier LLMsAlex Bouaziz, CEO and co-founder of Deel (Deel head-to-head tests against frontier LLMs across several use cases), X post, published Sep 25, 2026
- Jev vs. Kev: open-source Jev alternative tested side by sidefacethef, founder of Opper (self-described: 362 fresh test items run on Jev and Kev 4B through the same endpoint), Reddit post, r/LocalLLaMA, published Sep 25, 2026
- Decision Models vs. LLMs as Rubric Judges: Cheaper, Faster, and Wrong in the Same PlacesDelip Rao and Chris Callison-Burch, research paper authors (self-described: Nine rubric-judging panels from seven benchmarks with human judgments), Independent benchmark, arXiv, published Sep 24, 2026
- JevOut: Natural Context Can Flip Decision ModelsZixiang Xu and coauthors, research paper authors (self-described: Context-manipulation tests on four decision systems across seven datasets), Independent benchmark, arXiv, published Sep 24, 2026
- Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment FailuresRuoqi Guo, Yi Liu and coauthors, research paper authors (self-described: Alignment-failure detection across 44 benchmarks and five target models), Independent benchmark, arXiv, published Sep 24, 2026
- We Added Jev as a Reranker. Here's What We Learned.Ben Bartholomew, Hindsight team at Vectorize (self-described: Hindsight 0.10.1 recall with Jev as a reranker, measured on LoCoMo), Engineering blog post, Hindsight, published Sep 24, 2026
- The AI That Knows the Answer Before It Speaks [Jev Explained]Nir Diamant, DiamantAI (self-described: A bank fraud report and about 3,000 BANKING77 messages, Jev beside a chatbot model), Video, YouTube (DiamantAI), published Sep 24, 2026
- Same Scores, Different Decisions: Evaluating JEV and Language Models for Legal Document UnderstandingFan Zhang and 13 coauthors, research paper authors (self-described: ContractNLI evaluation of Jev and nine language models with repeated requests), Independent benchmark, arXiv, published Sep 23, 2026
- API: Cloudflare blocks valid /v1/systemone requests (HTML 403) when state text contains a curl commandjosebreijo, developer judging coding-agent text with System One (self-described: Agent-text judging service calling the HTTP API directly), GitHub issue, typesafe-ai/typesafe-sdk-js, published Sep 23, 2026
- I tested Semif (openjev) vs Von vs JevKingPinX, developer scoring decision models on a private repository (self-described: Four tasks labelled from the conventional-commit history of the author's Discord bot), Reddit post, r/LocalLLaMA, published Sep 23, 2026
- Jev isn't an LLM killer, and it isn't just a classifier. We put it in production with real users.NoSpecific64, founder of the agent startup Vestra (self-described: Vestra's agent harness, with real users running tasks daily), Reddit post, r/AI_Agents, published Sep 23, 2026
- How Jev cut the answer time in half for our smart search agentViktor Lidholt, founder of Serverpod (self-described: Starguide, Serverpod's documentation assistant, in production), Engineering blog post, Serverpod, published Sep 23, 2026
- JEV-as-a-Judge: Accept When Confident, Escalate When UnsureYubo Li, Yidi Miao, Ramayya Krishnan and Rema Padman, research paper authors (self-described: Judge evaluation against sixteen generative and reward-model judges with blinded human adjudication), Independent benchmark, arXiv, published Sep 22, 2026
- Replacing 10,000 Jev calls with one Opus 5.5 callnim, co-founder of dessn (self-described: dessn product pipeline), X post, published Sep 22, 2026
- Bookkeeping with JevAndy (@andywang), X user (self-described: A weekend build that fed Jev 34 months of a bookkeeping firm's work), X post, published Sep 22, 2026
- 299 real user intents tested Jev against production base lineSufficient_Flower860, developer of a Feishu life-assistant router (self-described: 299 real user intents from a production Feishu life-assistant router, 19 skills), Reddit post, r/AI_Agents, published Sep 22, 2026
- We benchmarked Jev-As-A-Judge for RAG Claim VerificationGPTeaheeMaster, developer verifying claims in a retrieval pipeline (self-described: 495 human-labelled claims from a retrieval pipeline), Reddit post, r/Rag, published Sep 22, 2026
- Spent the weekend stress-testing Jev on RAG pipelinesAcrobatic_Music_8484, builder of JevRAG (self-described: JevRAG, five retrieval decision steps with a calibration harness, tested on HotpotQA), Reddit post, r/Rag, published Sep 22, 2026
- I reverse-engineered Jev and rebuilt it as open weightss1lv3rj1nx, builder of openjev (self-described: openjev, an open-weights rebuild of a Jev-style model, tested against Jev on seven held-out schemas), Reddit post, r/LocalLLaMA, published Sep 22, 2026
- Jev System One (Cloud) vs Local Models (DistilBERT, ColBERT-v2, DeBERTa) on Legal Retrieval and Verificationazterizm, author of the Memon Systems benchmark (self-described: A UK legislation retrieval pipeline, 20 measured passes against local models on Apple Silicon), Reddit post, r/Rag, published Sep 21, 2026
- Introducing prompt_jev(): bringing Jev to MotherDuck SQLHamilton Ulmer, Till Döhmen and Jacob Matson, MotherDuck (self-described: prompt_jev() in MotherDuck SQL, benchmarked on 100,000 AG News rows), Engineering blog post, MotherDuck, published Sep 21, 2026
- Models watching modelsHrishi Olickel, author of Southbridge AI's engineering write-up (self-described: Southbridge Hankweave agent runs: 220,000 tool calls and 500 replayed runs), Engineering blog post, Southbridge AI, published Sep 19, 2026
- Feature: reuse/cache identical criteria across requests (prompt caching or registered questions) + expose cached_tokensmengoh-quandry, developer mapping security detection rules to MITRE ATT&CK with Jev (self-described: Fixed-taxonomy classification over about 700 MITRE techniques and sub-techniques), GitHub issue, typesafe-ai/typesafe-sdk-js, published Sep 19, 2026
- docs(landscape): Jev / TypeSafe System One, record don't-adopt decisionqte77, maintainer of doc-pipeline-engine (self-described: An adoption review for the doc-pipeline-engine project), GitHub issue, published Sep 19, 2026
- Jev on BANKING77: classification without task-specific fine-tuningsimonmesmith, independent researcher who published the protocol and every answer (self-described: All 3,080 BANKING77 test messages, pinned to jev-1.13.0), GitHub repository, published Sep 18, 2026
- Jev lost to Gemini on our email classification benchmarkNikhil Mudholkar, CTO and co-founder, Bryo (Bryo email classification benchmark: 1,565 business emails from industrial suppliers across 10 categories), X post, published Sep 17, 2026
- A day of benchmarking Jev against Brief's production judgesDrew Dillon, CEO and co-founder of Brief (Brief production judges: call typing, knowledge-graph relations, quality rubrics and code review), X post, published Sep 17, 2026
- jev-ultrafastBrowser Use, owner of the repository (self-described: jev-ultrafast, an open-source web agent where Jev picks each operation and element), GitHub repository, published Sep 17, 2026
- We're seeing extraordinary results from @typesafeaiGuillermo Rauch, CEO of Vercel (Vercel's fx auto mode, where a safety reviewer analyzes every command), X post, published Sep 16, 2026
- We benchmarked fx auto mode (safety) classifier with @typesafeai's JevPranit, builder of fx at Vercel (self-described: Vercel fx auto-mode safety classifier benchmark against GPT-5.6 Luna), X post, published Sep 16, 2026
Sep 2026 to Oct 2026.
129 sources from practitioners, by month and sentiment.
Where It Fits
Where does Jev belong in the stack?
Jev supports Model, Build, Data, Evaluate, and Operate.
- Business area
- Product & Engineering
- Function
- Software Development
- Operating stack
- AI Application Platform
- Primary role
- Structured Decision Model API
Model
Model APIs: Supports
Model APIs, supports. Jev is TypeSafe's System One model API: send state and typed questions to POST /v1/systemone and receive structured answers with probabilities and confidence.
Model gateway: Supports
Model gateway, supports. Jev can route an input to deterministic code, a specialist language model, or a human through typed intent questions; a gateway still owns provider routing and fallback policy.
Build
Orchestration: Touches
Orchestration, touches. Jev provides narrow decisions inside an agent loop, while orchestration remains in the team's framework.
Tool use: Supports
Tool use, supports. Choice and Noul answers can select a typed tool or function, while the application validates arguments and performs the call.
Data
Retrieval: Supports
Retrieval, supports. Jev can score or classify supplied state and retrieved passages, while retrieval and document ranking stay with the team's data layer.
Evaluate
Evaluation: Supports
Evaluation, supports. Confidence and probabilities make decision tests inspectable, but teams still need a workload-specific evaluation set and regression checks.
Operate
Observability: Touches
Observability, touches. The API returns token usage and model information, while request tracing, cost dashboards, and incident response stay in the team's observability stack.
Cloud deployment: Touches
Cloud deployment, touches. TypeSafe hosts the System One endpoint; deployment, regions, capacity planning, and failover remain platform responsibilities.
Guardrails: Supports
Guardrails, supports. Jev's guardrails recipe screens each message entering or leaving an LLM app with one typed request, and thresholds hazard and severity to pass, review, block, or route it.
Market mapThe layers Jev covers, and who else owns each one.
Model APIs
Model gateways & routing
- LiteLLM
- OpenRouter
- Portkey
- Vercel AI Gateway
Tool use & integrations
Retrieval & grounding
Evaluation & testing
4 more layers on the full map. Core, Supports and Touches describe coverage. They say nothing about quality.