Openlayer 记录了 48,415 月访问量，月度环比增长为 -6.4%，定价为免费增值，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。
Openlayer is a platform that tests AI systems before release, monitors them in production, and enforces policy and compliance requirements across every model and agent your company runs.
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 | openlayer.com | scale.com |
| 定价模式 | 免费增值，定价请咨询 | 定价请咨询 |
| 月访问量 | 4.84万 (48,415) | 61.69万 (616,915) |
| 月度环比流量变化 | -3303 (-6.4%) | +6.87万 (+12.5%) |
| 主要市场与份额 | 🇺🇸 美国 (44.1%) | 🇺🇸 美国 (44.2%) |
| 直接访问 / 月 | 2.59万 | 19.14万 |
| 用户评分 | 4.4 | 4.7 |
| 支持的平台 | 网站 | 网站 |
Openlayer is a platform that tests AI systems before release, monitors them in production, and enforces policy and compliance requirements across every model and agent your company runs.
Dozens of pre-built evaluations cover quality, safety, security, and performance, with LLM-as-a-judge scorers, session-level metrics, and support for writing your own custom tests against your own data.
Import a repository and run evaluation suites automatically on every change, benchmark each iteration, and block releases when a metric regresses beyond the threshold you define.
Trace every request through multi-step agent workflows, including tool calls and retriever steps, with token counts, latency, cost per request, alerting integrations, and subpopulation analysis.
Register each AI system with an owner, purpose, data sensitivity, and risk tier, score inherent risk across multiple dimensions, and move systems through staged approval gates before they reach production.
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.
专项更强Mindgard is an AI security platform that performs attacker-style reconnaissance, automated red teaming, and continuous testing of AI models, agents, and applications to find and fix exploitable vulnerabilities.
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AI 工程团队的协作层
在整个组织内统一 LLM 评估、可观测性与红队测试标准
