专项更强简化计算机视觉数据集标注与模型训练,但不太适合通用的 LLM 文本任务。
DataVLab 记录了 12,740 月访问量,月度环比增长为 -7.8%,定价为定价请咨询。Scale 记录了 616,915 月访问量,增长率为 +12.5%,定价为定价请咨询。
Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.
| 维度 / 指标 | ![]() | |
|---|---|---|
| 官方域名 | datavlab.ai | scale.com |
| 定价模式 | 定价请咨询 | 定价请咨询 |
| 月访问量 | 1.27万 (12,740) | 61.69万 (616,915) |
| 月度环比流量变化 | -1079 (-7.8%) | +6.87万 (+12.5%) |
| 主要市场与份额 | 🇺🇸 美国 (27%) | 🇺🇸 美国 (44.2%) |
| 直接访问 / 月 | 5125 | 19.14万 |
| 用户评分 | 4.2 | 4.7 |
| 支持的平台 | 网站 | 网站 |

面向受监管行业 AI 与机器学习团队的 ISO 27001 数据标注服务
提供边界框、多边形、分割掩码、关键点、地标点和分类标签,用于检测、分割与分类模型,每批数据均经人工校验。
逐帧框选、掩码、关键点和身份一致的目标轨迹,服务于检测、追踪与动作识别模型,并在序列层面完成验证。
3D 立方体、点云分割、可行驶区域标注和目标追踪,适用于机器人、自动驾驶、地理空间与工业 AI 项目。
文本区域标注、文档切分、手写体标注和结构化字段抽取,并提供量化评分标准下的 LLM 评估与生成式 AI 对齐数据。
Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.
Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.
专项更强简化计算机视觉数据集标注与模型训练,但不太适合通用的 LLM 文本任务。
专注于企业级数据标注和训练数据整理,类似于 Scale 的核心标注业务。
提供企业级多模态标注和数据管理工具,但对托管式标注人力的强调较少。

专项更强在互联环境中跟踪、评估并交付 AI 模型与智能体。

专项更强Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.
专项更强Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.

免费 / 开源提供灵活的开源替代方案,适用于自定义数据标注和人机回环(Human-in-the-loop)标注管道。
专项更强构建、模拟、评估并监控可自我改进的 AI 智能体

专项更强Provides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services.
专项更强Provides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services.
专项更强连接开发者与经过验证的真人参与者来进行 RLHF 和模型评估研究,而不是提供托管式标注。