由 Salesforce Data 360 与 Atlas 驱动的自主企业级 AI agent 与 CRM 智能。
由 Salesforce Data 360 与 Atlas 驱动的自主企业级 AI agent 与 CRM 智能。
RunningHub 记录了 3,105,554 月访问量,月度环比增长为 -28.5%,定价为免费增值。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。
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 | runninghub.ai | superannotate.com |
| 定价模式 | 免费增值 | 免费试用,定价请咨询 |
| 月访问量 | 310.56万 (3,105,554) | 38.6万 (386,034) |
| 月度环比流量变化 | -123.77万 (-28.5%) | +10.5万 (+37.4%) |
| 主要市场与份额 | 🇨🇳 中国 (52.7%) | 🇺🇸 美国 (31%) |
| 直接访问 / 月 | 229.72万 | 24.83万 |
| 用户评分 | 4.4 | 4.6 |
| 支持的平台 | 网站 | 网站 |

RunningHub is a cloud platform for running ComfyUI workflows online, building AI apps, and generating images and videos with hosted models and APIs.
Run, import, and share ComfyUI workflows in the cloud without local GPU hardware.
Publish a workflow as a single-click AI app that anyone can run with simple inputs.
Use hosted image and video models, including self-developed upscaling and enhancement tools, from one dashboard.
Integrate generation into your product via workflow, model, LLM, and app APIs.

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.
由 Salesforce Data 360 与 Atlas 驱动的自主企业级 AI agent 与 CRM 智能。
由 Salesforce Data 360 与 Atlas 驱动的自主企业级 AI agent 与 CRM 智能。
AI 驱动的虚拟主机平台,将基于提示的网站搭建与一键托管 OpenClaw 智能体部署相结合。

Muse is Meta's personal AI agent that takes on real everyday tasks — from sorting email and booking reservations to shopping, managing calendars and building fitness plans — using its own secure virtual computer in the cloud.
Miro is a collaborative visual workspace where distributed teams diagram, plan, and run workshops on an infinite canvas, now enhanced with AI that can generate diagrams, summaries, and prototypes from board content.

Airtable AI is the AI layer of the Airtable platform: Omni, a conversational app builder and data analyst, plus Field Agents that research, enrich, and generate content inside your workflows.
Airtable AI is the AI layer of the Airtable platform: Omni, a conversational app builder and data analyst, plus Field Agents that research, enrich, and generate content inside your workflows.
基于 Notion 的 Custom GPT 构建、管理与变现操作系统

TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.
TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.