400 companies matched to one candidate
这是 Sarvagya Kulshreshtha 公开的项目资料。本站按原始来源展示项目信息,用中文说明适用场景和阅读边界;项目名、源帖与代码保持原样,便于逐项核对。
这条案例记录了什么
Agent 与模型路由
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社区公开项目或作者演示
原始来源:Original showcase by Sarvagya Kulshreshtha。作者自述,本站未独立复现。
Sarvagya Kulshreshtha
记录日期:2026-09-18。日期与身份应以原始资料为准。
原始演示视频
视频来自此案例记录的原始媒体;播放内容和作者声明不等于本站复现。
怎样核对这个项目
- 先打开原始来源,确认作者、日期与 Jev 在项目中的具体用途。
- 如果提供仓库,再检查代码、运行要求和许可证;仓库存在不代表本站已经运行成功。
- 对速度、成本、准确率和规模数字,查看原文的任务、环境和计算口径。
- 路由候选是否完整。
- 模糊请求的回退分支。
- 完整任务成本与结果。
原始文字与技术细节
以下内容保留原语言,供核对事实。中文页的场景说明是阅读提示,不是逐句翻译或实测结论。
展开英文项目摘要与原帖
项目摘要
JEV is INSANE. We gave it 400 companies and one candidate profile. In 12 seconds, it predicted which jobs the candidate had the highest chance of getting, assigned a confidence score and detected job-candidate mismatches. All for just $0.0005 It can also score companies, analyse your experience, match you with the right roles and identify the opportunities you’re most likely to get based on your profile. Coming soon to @textbackdoor Comment “JEV” for early access.
来源原文
JEV is INSANE. We gave it 400 companies and one candidate profile. In 12 seconds, it predicted which jobs the candidate had the highest chance of getting, assigned a confidence score and detected job-candidate mismatches. All for just $0.0005 It can also score companies, analyse your experience, match you with the right roles and identify the opportunities you’re most likely to get based on your profile. Coming soon to @textbackdoor Comment “JEV” for early access.
原记录的限制
- Task accuracy is bounded by the precision of the defined candidate choices
- Third-party external dependencies and network latency may affect total workflow duration