Twelve Labs provides a holistic understanding of your videos, moving beyond the limitations of relying solely on individual types of data like keywords, metadata, or transcriptions. By simultaneously integrating all available sources of information, including images, sounds, spoken words, and on-screen text, the platform captures the complex relationships among these elements for a more human-like interpretation. The platform is designed to detect finer details frequently overlooked by single-modal methods, achieving a deeper understanding of video scenes beyond basic object identification. Additionally, it supports natural language queries, making interactions as intuitive as your daily conversations.

This approach offers several distinct advantages:

  • Improved accuracy: Integrating data across multiple modalities results in more accurate search results.
  • Natural interaction: Natural language querying provides a more intuitive search experience. Instead of relying on specific keywords or tags, you can express your search queries in plain language, mirroring everyday communication.
  • Less contextual errors: Analyzing multiple aspects of a video reduces the likelihood of misinterpreting context, leading to more reliable search results.
  • Time Efficiency: You don't need to watch entire videos or rely on possibly incomplete metadata to locate the content you're looking for. The platform can quickly search vast amounts of video data, returning only the relevant clips in response to your query.

A search request is submitting one or more queries to retrieve relevant video content. Each query specifies a request for information. You can execute queries individually or combine multiple queries into a single search request using logical operators, allowing for more nuanced and targeted search results. Depending on your use case, proceed to one of the following pages: