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Agent-Native vs TypeSafe AI - Jev
Agent-Native 记录了 52,065 月访问量，月度环比增长为 +90.7%，定价为免费。TypeSafe AI - Jev 记录了 6,148,688 月访问量，增长率为 -36.4%，定价为付费。
Agent-Native 记录了 52,065 月访问量，月度环比增长为 +90.7%，定价为免费。TypeSafe AI - Jev 记录了 6,148,688 月访问量，增长率为 -36.4%，定价为付费。
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.
| 维度 / 指标 |  | |
|---|---|---|
| 官方域名 | agent-native.com | typesafe.ai |
| 定价模式 | 免费 | 付费 |
| 月访问量 | 5.21万 (52,065) | 614.87万 (6,148,688) |
| 月度环比流量变化 | +2.48万 (+90.7%) | -351.3万 (-36.4%) |
| 主要市场与份额 | 🇺🇸 美国 (98.6%) | 🇺🇸 美国 (26.4%) |
| 直接访问 / 月 | 2.26万 | 314.11万 |
| 用户评分 | 4.4 | 4.2 |
| 支持的平台 | 网站 | 网站 |
开源 TypeScript 框架：智能体与界面共享同一套能力
用 defineAction() 声明一次能力，智能体、React 界面、HTTP 客户端与集成即可自动调用同一段代码，无需重复实现。
智能体可感知用户正在浏览、选择与编辑的内容，双方读写同一个 PostgreSQL 数据库，共享唯一事实来源。
为智能体提供可复用的专业知识、持久上下文与长期记忆，减少重复解释与重复犯错。
支持按计划或事件自动运行智能体任务，并可在同一工作区或跨互联智能体委派给专职智能体。
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.
Jev outputs typed decisions that application code can act on directly, rather than prose that must be parsed and interpreted.
Every decision carries an estimate of how confident the model is, so you can set thresholds for autonomous action versus human escalation.
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.
Because confidence estimates expose uncertainty, Jev is designed to avoid hallucination-style failures in automation, enabling zero-hallucination decision paths where confidence is high.
Google 的快速原型开发 IDE 与开发者 API 工作台，用于构建基于 Gemini 模型的多模态应用。
免费 / 开源Provides an open-source framework for building agent workflows, but requires manual implementation of calibrated decision-scoring logic.
