Foundation video models
Build varied records across selected subjects, activities, formats, markets, and time windows.
- Long-form and short-form media
- Defined diversity dimensions
- Training and evaluation splits
01 · 定义Describe the model moment
Turn abstract coverage goals into subjects, actions, settings, languages, and timeframes.
02 · 检查Review the complete record
See the media, transcript, provenance, metadata, and acceptance state before volume expands.
03 · 运营Keep supply moving
Choose a one-time collection or recurring delivery while WebScrapingAPI runs the data operation.
适合工作负载
建立媒体供应围绕模型工作.
开始从你的团队需要数据支持的决定.
Video language models
Align visual sequences with captions, transcripts, and contextual metadata for multimodal models.
- Timestamped text context
- Clip-level observations
- Source-linked records
Speech and audio systems
Separate audio from relevant video sources while retaining language, source, and timing context.
- Audio tracks and captions
- Language and domain filters
- Aligned media identifiers
Physical AI and world models
Collect scenario-led clips where actions, environments, point of view, and time boundaries matter.
- Robotics scenarios
- Autonomous mobility contexts
- Action-focused segments
数据简报
更多视频 作为可测量的请求.
简单描述您的模型团队需要看到的证据,不仅仅是网站列表. 我们将这一目标转化为可搜索的标准,接受规则和您的团队可以评估的记录合同.
Bring us your target scenariosModel objective
Training, fine-tuning, evaluation, or retrieval.
Scenario
Subjects, actions, events, domains, and environments.
Media profile
Duration, resolution, orientation, audio, and point of view.
Coverage mix
Markets, languages, time windows, and source categories.
Fields and sample records
Files, transcript, metadata, labels, and provenance.
Supply horizon
One-time build, recurring refresh, or continuous intake.
发现和选择
找合适的时刻,而不是仅仅提到它们的页面.
结合源码标准和媒体级信号,以便审查人员可以看到每个候选人为什么属于该计划.
Filter dimensions
Subject and actionwhat appears or happens
Environmentsetting and conditions
Language and marketspeech and source context
Time windowpublication and capture date
Media profileduration, orientation, quality
Candidate reviewKitchen task · overhead preparation
3 shortlisted植物制备序列overhead · 00:42 · en-US
- action match
- clean view
- audio present
材料组装教程angled view · 01:08 · en-GB
- subject match
- captions present
商业厨房示范wide view · 00:35 · de-DE
- action match
- market match
记录输出
保持每种模式均符合一个稳定的记录.
交付可以保存原始媒体文本,同时只包装您下游工作流需要的组件.
Video and selected clips
Source media or selected segments with stable identifiers and timeframe context.
Audio and transcript
Aligned audio tracks, available captions, or program-defined transcript outputs.
Metadata and provenance
Source URL, capture time, media attributes, filter context, and record state.
Manifest and quality state
A machine-readable inventory that connects files, fields, versions, and acceptance results.
运营数据供应
你的团队定义了信号,我们负责媒体运营.
WebScrapingAPI为管理程序运营采集,提取,剪辑准备,质量监测,源变换维护和交付.
Translate the brief
WSATurn model requirements into sources, discovery criteria, record fields, and acceptance rules.
Build and review a sample
Shared reviewGive data and model teams representative media records to inspect together.
Operate collection
WSARun source connectors, media capture, extraction, segmentation, and record assembly.
Monitor and deliver
WSATrack collection health, validate the defined quality rules, and package each delivery.
交付设计
让供应量适应训练管道.
每批货都带有可预测的文件,识别器,元数据和明示在选择的安全目的地.
Source files or selected clips, organized by stable record identifier.
Transcripts, captions, source context, and defined descriptive fields.
Record inventory, versions, acceptance results, and exception states.
Packaged for the storage or ingestion path selected with your team.
开始的方法
选择最短的路径,
开始从一个准备的包装,形成一个可重复的收藏,或者把整个供应操作交给.
AI Data Packages
Begin with an existing data family when its source mix, schema, history, and media coverage match your workload.
- Review sample records
- Select a delivery snapshot
- Move quickly into evaluation
Recurring video supply
Set the scenario mix, sources, record contract, quality rules, and refresh cadence for a repeatable program.
- Model-specific brief
- Consistent record design
- One-time or recurring delivery
Managed collection
Let WebScrapingAPI run source discovery, collection, media preparation, quality monitoring, and delivery.
- A managed collection service
- Source-change maintenance
- Delivery-ready records
计划定价
数据供应的价格不是抽象的媒体数量.
您将分享您的优先场景和交付视野. 我们将围绕发现,准备,验证和提供有用记录所需的工作制定计划.
What shapes the program
01Scenario specificity如何定义行动,环境和媒体资料.
02Source and coverage mix资源,市场,语言,时间窗户,多样性尺寸.
03Record preparation剪辑,音频分离,转录,元数据,质量规则.
04Delivery horizon一次数据集,反复更新或连续收集程序.
What can a video data record include?
Each accepted record can include the source video or selected clip, audio, transcript or captions, thumbnail, source URL, capture time, and the metadata fields defined for your program.
Can delivery be one-time or recurring?
Yes. Choose a one-time dataset for a defined training or evaluation window, or recurring delivery when the source universe and model program need fresh records over time.
How do we define the right video coverage?
Start with the model task, subject matter, actions, environments, markets, languages, dates, duration range, point of view, and media quality that matter. WebScrapingAPI turns those priorities into a measurable collection brief and sample set.
Who maintains collection and quality?
WebScrapingAPI handles collection, extraction, clip preparation, quality monitoring, source-change maintenance, and delivery for the managed program. Your team reviews samples and accepts the record design before production.
Where can the data be delivered?
Records are packaged for a selected secure destination with a clear manifest, stable identifiers, and the media and metadata layout chosen for your downstream pipeline.
How do we evaluate fit before launch?
Share a representative brief and priority scenarios. We return a sample plan that lets your data and model teams review coverage, media quality, record structure, and delivery shape before selecting a production path.
Is this the same as VLA video data?
VLA programs add action, environment, point-of-view, and time-boundary requirements for physical AI workloads. Use the dedicated VLA Video Data page when robotics, autonomous mobility, or world models are central to the brief.
开始使用代表性媒体
让我们知道你的模型需要从哪些时刻学习.
带来您的优先场景,覆盖面积,以及您喜欢的记录形状.