Appen 每月有 665,840 次造訪,月增率 +0.2%,定價模式為需聯絡報價。Text2Cron 每月有 70 次造訪,成長率 -96.7%,定價模式為付費。
| 面向/指標 | ![]() | ![]() |
|---|---|---|
| 官方網域 | appen.com | text2cron.com |
| 定價模式 | 需聯絡報價 | 付費 |
| 每月造訪次數 | 66.58萬 (665,840) | 70 (70) |
| 月流量變化量 | +1103 (+0.2%) | -2041 (-96.7%) |
| 主要市場與市佔 | 🇺🇸 美國 (22%) | 🇵🇪 秘魯 (60.4%) |
| 每月直接造訪 | 23.83萬 | 26 |
| 使用者評分 | 4.4 | 4.2 |
| 支援平台 | 網站 | 網站 |

為前沿 AI 模型提供人工驗證的訓練資料與評估服務
思維鏈推理軌跡、專家級 RLHF、監督式微調示範與對抗性紅隊資料,服務於能力最強的模型。
黃金軌跡、RL 環境設計、失敗模式分類法,以及基於軟體工程任務的代理深度評估。
多語 ASR 與會話語音資料、表現力 TTS 標註、視覺語言模型訓練資料、影片動作標註與語音助理評估。
LiDAR 點雲標註、多鏡頭感測器融合、機器人示範軌跡、世界模型推演與具身互動日誌。

Text2Cron is a browser-based converter that translates plain English scheduling requests — like "every weekday at 6 AM" or "first day of every month" — into standard Unix cron expressions you can copy straight into crontab, Kubernetes manifests or CI pipelines.
Type a schedule in plain English — 'every weekday at 2 PM', 'every 30 minutes', '15th of each month at 3 PM' — and receive a standard five-field cron expression to copy.
The site states all conversion happens in your browser with no scheduling data stored or transmitted to external servers, keeping infrastructure details private.
Output targets standard Unix cron format, working across Linux crontab, Vixie cron, macOS cron, AWS EventBridge, Kubernetes CronJobs and CI/CD pipeline definitions.
Documents each cron field, explains special characters like *, /, L, W and #, and shows conversions for time-based, day-based and monthly schedules.
免費 / 開源用一句話描述就能打造可用的應用、網站與 AI 代理

結合自訂軟體與專門的專家團隊來處理複雜業務,但屬於量身訂製的服務。
提供先進的多模態資料策展與標註基礎設施,但標註工作需要自備人力。


免費 / 開源Provides a flexible open-source annotation platform for self-hosting, but lacks Appen's managed enterprise human workforce services.
免費 / 開源Provides a flexible open-source annotation platform for self-hosting, but lacks Appen's managed enterprise human workforce services.

Supplies expert human annotators for specialized training and evaluation datasets, but operates at a smaller scale.
Supplies expert human annotators for specialized training and evaluation datasets, but operates at a smaller scale.