What are System One Models?

System One Models are a class of AI model built to make decisions inside software rather than converse with people. They return typed outputs and calibrated confidence instead of free-form text.

Jev is TypeSafe's first public System One Model, optimised for automation. You send it structured questions and it returns typed decisions with probabilities and confidence estimates that your software can act on.

Is Jev just a smaller LLM with structured output?

No. Jev uses a new architecture, a new sampler and a new training algorithm called Reinforcement Learning for Calibrated Decisions (RLCD). It is not a smaller LLM with a JSON wrapper — it is designed around typed decisions and calibrated confidence from the ground up.

How is this different from a standard LLM with JSON mode?

General-purpose LLMs return words for people. Jev returns decisions that software consumes directly, more like code: reliable, fast, self-consistent and type-safe, with a confidence estimate attached to every decision.

How do I get started and what does Jev cost?

Jev is in early access, and TypeSafe says it costs $42 per billion input tokens, which it describes as roughly 238x lower input pricing than comparable frontier chat models. You can request access through the site's API console and explore the documentation.

TypeSafe AI - Jev 的每月流量與成長趨勢為何？

TypeSafe AI - Jev 目前每月有 614.87萬次造訪，月流量變化為 -351.3萬（成長率 -36.4%）。其主要來源市場為美國（佔比 26.4%），其中包含每月 314.11萬次直接造訪與每月 — 次自然搜尋造訪。

TypeSafe AI - Jev 是免費的嗎？其定價模式為何？

TypeSafe AI - Jev 採用付費定價模式。Paid, with early access to Jev. TypeSafe quotes Jev at $42 per billion input tokens and describes this as roughly 238x lower input pricing than comparable frontier chat models. Enterprise options and API access are arranged through the company, alongside documentation and an API console. 支援的帳務與結帳平台包括：未列出。

TypeSafe AI - Jev — 月造訪量 (614.87萬/月)、定價、API 與替代方案

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TypeSafe AI - Jev — 月造訪量 (614.87萬/月)、定價、API 與替代方案 | Open AI Tools

關於 TypeSafe AI - Jev

Typed decisions, not strings

Jev outputs typed decisions that application code can act on directly, rather than prose that must be parsed and interpreted.

Calibrated confidence on every call

Every decision carries an estimate of how confident the model is, so you can set thresholds for autonomous action versus human escalation.

Reported 193x faster, 444x cheaper

TypeSafe reports Jev at roughly 193x faster and 444x cheaper than LLM-based workflows on comparable System One tasks, with a price of $42 per billion input tokens.

Built to reduce hallucination

Because confidence estimates expose uncertainty, Jev is designed to avoid hallucination-style failures in automation, enabling zero-hallucination decision paths where confidence is high.

Composable workflows with human-in-the-loop

Combine Jev's per-call decisions inside your own code to construct larger workflows, with explicit control over when intelligence acts and when it defers to a human.

TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.

TypeSafe AI - Jev 的高效使用情境

Engineering teams automating decisions

Build reliable automation workflows

Replace text-generating model calls with typed decisions and confidence scores so pipelines can auto-approve clear cases and route ambiguous ones to a human, as in the reported 88% screening cost reduction case study.

Developers adding AI to products

Add decision intelligence to an app

Classify and triage incoming items with low latency and low cost, escalating only the cases where confidence is below your threshold.

AI and data platform teams

Run high-throughput classification

Insert a high-speed, low-cost model into automated data and content pipelines where decisions must be consistent and confidence-graded.

Researchers and ML engineers

Benchmark decision models

Evaluate Jev's typed, calibrated outputs against existing LLM calls to compare latency, cost and reliability before wider rollout.

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排名	AI 工具	每月造訪次數	月增幅	直接流量占比	價格	正面對決
●	TypeSafe AI - Jev	614.87萬	-36.4%	51% 直接流量	付費	目前產品
1	Jev AI 提供結構化且帶機率分數的決策建模 API，很符合 TypeSafe AI 專注於校準自動化的特點。	2.96萬	+117.4%	39% 直接流量	免費	對比 Jev AI
2	RightNow AI 能從多模態輸入提供串流決策機率，但偏向即時資料流而非靜態型別決策。	8356	-39.9%	40% 直接流量	免費增值、付費	對比 RightNow AI
3	Not Diamond 最佳化程式碼代理的模型路由，但缺乏 TypeSafe AI 專屬的型別決策評分與軟體自動化特色。	2.92萬	+25.3%	43% 直接流量	免費增值、付費、需聯絡報價	對比 Not Diamond
4	Emergence AI 部署企業級受管制的多代理網路，但著重於更廣泛的代理協同編排，而非獨立的型別決策。	5.47萬	-43.1%	32% 直接流量	需聯絡報價	對比 Emergence AI
5	Decisions 結合企業流程自動化與商業規則，但缺乏原生機器智慧信賴度評分 API。	9.1萬	+14.6%	18% 直接流量	需聯絡報價	對比 Decisions
6	OpenRouter 透過單一 API 提供多種基礎模型存取，但缺乏專門的型別決策評分與信賴度指標。	1994.14萬	-6.2%	60% 直接流量	付費	對比 OpenRouter