Physical AI / VLA

Video data for models
that act in the real world.

Humanoid robots, autonomous vehicles, and world models all need the same thing: massive, diverse video of real-world physics and human activity. We deliver continuous, task-targeted web video clips + metadata at petabyte scale.

Video Data Feed
Live
Total clips ingested 1,284,930
10B+
Videos extracted (and counting)
10PB+
of video provided to leading AI teams daily
90PB
Web archive
195
Countries covered
99.99%
Uptime SLA

Trusted by 75% of AI labs and 20,000+ companies

SOC 2TYPE II
ISO27001
GDPR
CSASTAR
CCPA
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Use Cases

One data layer for every
physical AI modality.

Whether you're training a robot arm, a self-driving stack, or a foundation world model, the pipeline is the same: discover, extract, deliver.

Humanoid Robotics

Task-family targeted video of human manipulation, locomotion, and object interaction. Replace the teleoperation bottleneck with web-scale demonstrations that enable zero-shot generalization.

Kitchen tasks: wipe, place, pour
Warehouse: pick, sort, pack, stack
Assembly: insert, fasten, align
Autonomous Vehicles

Diverse driving footage across geographies, weather conditions, and traffic scenarios. Edge cases your simulation fleet can't generate: construction zones, unmarked roads, emergency vehicles.

Urban intersections and roundabouts
Highway merges and lane changes
Adverse weather: rain, fog, snow, night
World Models

Rich video of real-world physics for training predictive models that understand how objects move, deform, and interact. The visual prior your world model needs to predict what happens next.

Object dynamics: fall, slide, bounce
Fluid and soft-body interactions
Multi-object scenes with occlusion

Need a custom scenario pipeline?

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How It Works

Define. Search. Extract.

Three steps from scenario definition to a pipeline-ready video stream.

1 Define

Specify your target scenarios: task families for robotics, driving conditions for AV, or physical interactions for world models. We map your requirements to discovery filters across our 90 PB Web Archive.

2 Search

Filter massive web-scale video archives by environment, lighting, camera angle, action type, and more. Surface high-quality demonstrations that match your exact training requirements.

3 Extract

Isolate relevant footage, extract action-specific scenes, and deliver pre-cut MP4 clips with structured metadata and precise timeframes — ready to plug into your training pipeline.

Platform

Continuous, targeted web video
for physical AI training.

Find moments before you download.

Visual indexing & High-granularity filtering to surface exactly the demonstrations, driving footage, or physical interactions your model needs.

High-Granularity Filtering

Search and filter through massive web archives to find fresh video sources that match your specific scenario requirements.

Metadata-based discovery

Surface new sources through rich, filterable metadata including modality, environment type, camera angle, and domain context.

Precise targeting

Pinpoint videos by specific conditions: "rainy highway merges", "low-light kitchens", "industrial assembly lines".

SCENARIO FILTER
"Kitchen manipulation"47,328 clips
"Highway driving rain"23,891 clips
"Object collision"14,203 clips
"Warehouse pick+place"31,892 clips
"Parking lot maneuver"18,441 clips

Web-scale video beats simulation.

Real-world footage provides the visual diversity and physics grounding that synthetic data and teleoperation cannot match, at a fraction of the cost.

Environmental Diversity

Unmatched coverage across lighting, locations, weather, camera angles, and edge cases that simulation or teleoperation cannot generate at scale.

Scenario-Specific Ingestion

Focus on high-value scenes: manipulation tasks, driving scenarios, or physical interactions. Reduces noise in your training data.

Pipeline-Ready Output

Pre-cut MP4 clips delivered with structured metadata and precise timeframes. Drop directly into your training framework without preprocessing.

EXPORT FORMATS
MP4 video clips
Pre-cut, scenario-targeted clips ready for ingestion.
Structured metadata
Scenario type, environment context, camera POV, actions, and geo region.
Precise timeframes
Start/end timestamps for every clip so you extract exactly what you need.
METADATA PER CLIP
{ scenario_type, env_context,
  camera_pov, actions[],
  start_ms, end_ms, fps,
  geo_region }

Continuous delivery at any throughput.

The infrastructure layer your physical AI team can rely on. Automated, compliant, and built for production-scale data ingestion.

High-Volume Resilience

Automated handling of HTTP 429 errors, blocks, and anti-bot flows to ensure continuous data delivery without interruption.

Compliance & Security

Fully compliant global access. Raw video + metadata delivered directly to your secure cloud. SOC 2 Type II certified.

Standardized Metadata

Consistent schema for temporal alignment, coordinate normalization, and action segmentation out of the box.

99.99%Uptime SLA
2PB+Video delivered to AI teams daily
195Countries in IP network
400M+ monthlyIP addresses for unblocking

75% of world's leading AI Labs use Bright Data

Talk to an expert
Why Web Video

Real-world video beats
every alternative.

Simulation has a domain gap. Teleoperation doesn't scale. Fleet data is narrow. Web-scale video gives your model the diversity it needs to generalize.

Teleoperation

Expensive, slow to scale, and limited in diversity — you're constrained to what your operators can physically demonstrate.

Web video: 1000x cheaper per clip, infinite environmental variety.

Simulation

Synthetic domain gap. Physics approximations degrade transfer.

Web video: real physics, real materials, real lighting. No sim-to-real gap.

Fleet data

Narrow distribution. Only your vehicles, your routes, your conditions.

Web video: every geography, every weather condition, every edge case.

FAQ

Common questions

yt-dlp is an open-source tool designed for downloading individual videos. Bright Data Media extraction API is purpose-built for multimodal training, VLM, and VLA pipelines at scale — continuous delivery of targeted MP4 clips with structured metadata, at petabyte throughput, with compliance built in.
Web Unlocker automatically resolves HTTP 429 errors by distributing requests across our global IP pool of 400M+ monthly addresses. Unlike standalone yt-dlp which fails on 429 errors, our API automatically retries with different IP addresses and optimal timing.
This error occurs when platforms detect automated patterns. Web Unlocker prevents detection through AI-powered browser fingerprinting that mimics real user behavior. Your extraction continues without human intervention.
Yes. Use Filter API to identify and filter content by language, duration, upload date, format, and other parameters before extraction. Build targeted lists that match your exact training data criteria, then extract with Media extraction API.
Video is delivered as MP4 clips with structured metadata and precise timeframes. Data can be sent to S3, GCS, Azure Blob, or via direct download.
Bright Data collects only publicly available data and operates under strict compliance policies. We hold SOC 2 Type II, ISO 27001, and are fully GDPR and CCPA compliant. In 2024, we won court cases against Meta and X in U.S. federal court, setting legal precedent for ethical web data collection.
Yes. We offer academic licensing and research pricing for universities and non-profit research labs. Contact us to discuss your specific needs and volume requirements. Sample files are available for all data types at no cost.
Datasets are priced by category, volume, and delivery cadence. One-time snapshots are cheapest. Recurring and continuous feeds are priced per-delivery. Enterprise plans include volume discounts and custom SLAs. Contact us for a quote tailored to your training run.

Book a Demo

We'll demonstrate sourcing and discovery of high-fidelity videos, to stream directly into your training pipeline.