Bright Data Video Data

Founded by Or Levi in 2014

Extract petabyte-scale video, audio, and metadata for AI model training

Cost

Free Trial

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Time to value

Requires Expertise

You can use Bright Data to collect large-scale video, audio, captions, and metadata from across the web for training LLMs, vision-language models, and world models. It lets you filter content by language, domain, duration, and geography, then extract pre-cut MP4 clips with structured metadata delivered directly to S3, GCS, Azure, or Snowflake. It bypasses anti-bot measures and rate limits at scale, making it an alternative to yt-dlp for teams building multimodal AI training pipelines.

What Bright Data Video Data does

Define video extraction parameters including modality, language, domain, and output formatFilter candidate videos by duration, upload date, quality, geographic region, and lighting conditionsExtract MP4 video clips pre-cut to specified timeframes with attached structured metadataSeparate and download audio tracks in m4a format aligned to video timestampsDeliver extracted data automatically to S3, GCS, Azure Blob, Snowflake, or via webhookSet up continuous video feeds that stream newly published content to cloud storageBypass anti-bot protections and rate limiting using a global IP pool of 400M+ addressesPreview and validate sample clips before scaling up a full extraction pipelineExtract pre-cut MP4 clips with precise timeframes and structured metadata ready for trainingFilter video content by language, duration, geography, upload date, and lighting before downloadingBypass anti-bot measures, CAPTCHAs, and HTTP 429 rate limit errors automaticallyDeliver video data directly to Amazon S3, Google Cloud Storage, Azure Blob, or SnowflakeAccess a 90PB web archive for historical video discovery and contextSeparated audio tracks in m4a format aligned to video timestamps for ASR trainingNative captions, transcripts, and subtitles in hundreds of languages time-aligned with videoContinuous streaming feeds that push new video to your cloud as it is published