Scale: 提供大規模的企業級標註與模型評估,但通常需要比 Labelbox 更高的企業預算。 Labelbox 每月有 762,803 次造訪,月增率 -22.8%,定價模式為需聯絡報價。Scale 每月有 616,915 次造訪,成長率 +12.5%,定價模式為需聯絡報價。
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.
| 面向/指標 | ![]() | |
|---|---|---|
| 官方網域 | labelbox.com | scale.com |
| 定價模式 | 需聯絡報價 | 需聯絡報價 |
| 每月造訪次數 | 76.28萬 (762,803) | 61.69萬 (616,915) |
| 月流量變化量 | -22.52萬 (-22.8%) | +6.87萬 (+12.5%) |
| 主要市場與市佔 | 🇺🇸 美國 (21.9%) | 🇺🇸 美國 (44.2%) |
| 每月直接造訪 | 37萬 | 19.14萬 |
| 使用者評分 | 4.4 | 4.7 |
| 支援平台 | 網站 | 網站 |

前沿 AI 訓練所用的環境,以及負責例行工作的代理
涵蓋視覺、語言與生成任務的結構化標註、資料策展、模型評估與人機協作審閱,是訓練與評估資料的基礎。
Recursion 代理會從建置、告警、提交、檢查點與排程自動啟動,並在背景持續工作直到任務完成可審查。
專業代理涵蓋軟體工程、可靠性、資安、ML 研究、評估、研發、產品與財務,從修復不穩定測試到撰寫事故檢討草稿。
每次執行都由評分代理打分,評分後的工作階段留下記憶、筆記與技能,供下一次執行前讀取。
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.
提供企業級多模態標註與資料管理工具,但較不強調託管式的標註人力。

專項更強在互聯環境中追蹤、評估並交付 AI 模型與代理。

專項更強Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.
專項更強Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.

免費 / 開源提供具彈性的開源替代方案,適用於自訂資料標註與真人迴路(Human-in-the-loop)標註管線。
專項更強打造、模擬、評估並監控能自我改進的 AI 代理

專項更強Provides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services.

專項更強Focuses strictly on LLM evaluation, testing, and observability rather than raw data annotation and training dataset curation.
專項更強Focuses strictly on LLM evaluation, testing, and observability rather than raw data annotation and training dataset curation.

Provides efficient smart annotation tools and managed labeling services, but has a smaller ecosystem for complex enterprise agent workflows.
Provides efficient smart annotation tools and managed labeling services, but has a smaller ecosystem for complex enterprise agent workflows.