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
Multimodal training data
Video Data for AI Training
Turn a defined model objective into curated video records with aligned audio, transcripts, clips, and metadata—delivered once or kept current as your program evolves.
01 · DefineDescribe the model moment
Turn abstract coverage goals into subjects, actions, settings, languages, and timeframes.
02 · InspectReview the complete record
See the media, transcript, provenance, metadata, and acceptance state before volume expands.
03 · OperateKeep supply moving
Choose a one-time collection or recurring delivery while WebScrapingAPI runs the data operation.
Workload fit
Build the media supply around the model job.
Different model programs need different moments, modalities, and context. Begin with the decision your team needs the data to support.
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
The data brief
Make “more video” a measurable request.
A useful brief describes the evidence your model team needs to see—not only a list of websites. We translate that goal into searchable criteria, acceptance rules, and a record contract your team can evaluate.
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.
Record contract
Files, transcript, metadata, labels, and provenance.
Supply horizon
One-time build, recurring refresh, or continuous intake.
Discovery and selection
Find the moments that match—not just the pages that mention them.
Combine source criteria with media-level signals so reviewers can see why each candidate belongs in the program.
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 shortlistedVegetable preparation sequenceoverhead · 00:42 · en-US
- action match
- clean view
- audio present
Ingredient assembly tutorialangled view · 01:08 · en-GB
- subject match
- captions present
Commercial kitchen demonstrationwide view · 00:35 · de-DE
- action match
- market match
Record outputs
Keep every modality aligned to one stable record.
Delivery can preserve the original media context while packaging only the components your downstream workflow needs.
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.
Operated data supply
Your team defines the signal. We run the media operation.
WebScrapingAPI operates collection, extraction, clip preparation, quality monitoring, source-change maintenance, and delivery for the managed program.
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.
Delivery design
Fit the supply to your training pipeline.
Each batch arrives with predictable files, identifiers, metadata, and a manifest at the selected secure destination.
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.
Ways to start
Choose the shortest path to useful video records.
Start from a prepared package, shape a repeatable collection, or hand off the complete supply operation.
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.
- Named operating ownership
- Source-change maintenance
- Delivery-ready records
Program pricing
Price the data supply—not an abstract media count.
Share your priority scenarios and delivery horizon. We will shape a plan around the work needed to discover, prepare, validate, and deliver useful records.
What shapes the program
01Scenario specificityHow narrowly actions, environments, and media profiles are defined.
02Source and coverage mixSources, markets, languages, time windows, and diversity dimensions.
03Record preparationClipping, audio separation, transcripts, metadata, and quality rules.
04Delivery horizonOne-time dataset, recurring refresh, or continuous collection program.
Buyer questions
Evaluate the program with your data and model teams.
Clear answers on record contents, coverage design, operating ownership, delivery, and next steps.
Ask a video data specialistWhat 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.
Start with representative media
Show us the moments your model needs to learn from.
Bring your priority scenarios, coverage dimensions, and preferred record shape. We will turn them into a sample plan your team can inspect.