Sieve 记录了 124 月访问量，月度环比增长为 +1.6%，定价为定价请咨询。SuperAnnotate 记录了 386,034 月访问量，增长率为 +37.4%，定价为免费试用，定价请咨询。
Sieve is a data lab that supplies multimodal video, audio and interaction datasets — egocentric demonstrations, multi-camera studio recordings, robotics evaluations and large-scale media — to frontier AI teams.
SuperAnnotate is an AI data platform that combines a collaborative multimodal annotation editor, an expert data-operations team, and the orchestration layer needed to move curated datasets into training, evaluation, and production pipelines. It is aimed at teams building computer vision, NLP, audio, and generative AI systems who need reliable, high-quality ground truth at scale.
| 维度 / 指标 | | |
|---|---|---|
| 官方域名 | sievedata.com | superannotate.com |
| 定价模式 | 定价请咨询 | 免费试用，定价请咨询 |
| 月访问量 | 124 (124) | 38.6万 (386,034) |
| 月度环比流量变化 | +2 (+1.6%) | +10.5万 (+37.4%) |
| 主要市场与份额 | 🌐 全球 (—) | 🇺🇸 美国 (31%) |
| 直接访问 / 月 | 54 | 24.83万 |
| 用户评分 | 4.1 | 4.6 |
| 支持的平台 | 网站 | 网站 |
Sieve is a data lab that supplies multimodal video, audio and interaction datasets — egocentric demonstrations, multi-camera studio recordings, robotics evaluations and large-scale media — to frontier AI teams.
First-person recordings of economically valuable physical work, paired with hand-pose, motion and synchronised sensor annotations.
Multi-camera video and audio collection with bespoke rigs and controlled environments built to a client's specification.
Both simulated and real-world test suites that measure how well robot policies perform across tasks and conditions.
Petabyte-scale synchronised video and audio datasets, including published engineering work on embedding a billion videos for retrieval.
SuperAnnotate is an AI data platform that combines a collaborative multimodal annotation editor, an expert data-operations team, and the orchestration layer needed to move curated datasets into training, evaluation, and production pipelines. It is aimed at teams building computer vision, NLP, audio, and generative AI systems who need reliable, high-quality ground truth at scale.
One configurable annotation surface for image, video, text, and audio projects, so multimodal datasets can be labeled without switching tools.
Search, filter, and inspect datasets to find the examples that will most improve a model, then route them into targeted annotation or review queues.
Dashboards for annotation volume, reviewer agreement, and project progress, plus advanced analytics on upper tiers for program-level reporting.
Metered orchestration capacity for running annotation, evaluation, and data-processing workloads, scaled by plan from roughly 1K to 10K compute hours.
强大的企业级数据标注与智能体自动化，但采用不同的协作界面和定价结构。
专项更强Extensive human-validated training datasets and alignment services, but lacks SuperAnnotate's self-serve software platform flexibility.
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.
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.
专项更强Exceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments.
专项更强Exceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments.
具备优秀的计算机视觉多模态数据基础设施，但缺少 SuperAnnotate 的部分更全面的企业项目管理工具。
免费 / 开源一个通用 API，接入 500+ AI 模型与 1,000+ 智能体工具
免费 / 开源面向具身智能与机器人训练的视频数据基础设施
专项更强Strong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling.
专项更强Strong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling.
免费 / 开源强大的开源数据标注，支持深度自定义，但需要自行托管且缺乏现成的托管企业工作流。
