Lights, Camera, Extraction: Navigating Video Data to Build Foundation Models

Sourcing video training data remains one of the most complex challenges in building effective AI systems.

Whether you're training a model to understand context, emotion, or behavior, the right video dataset can make or break performance. But video content is large, diverse, and often locked behind opaque licensing or regulatory hurdles, slowing progress for even the most advanced teams.

This guide demystifies the video data landscape for AI builders. It breaks down the full range of content types —from raw and user-generated footage to enterprise video and synthetic data —explaining where to find them, how to assess their quality, and what to consider from a legal, ethical, and operational standpoint. It’s a practical roadmap for anyone seeking to unlock video’s full potential for AI.