Brightcove Enhances Video Cataloging with New Custom Metadata Fields

The ability to define custom metadata fields provides greater flexibility for content owners to categorize and manage their video libraries. This can improve content discoverability and operational efficiency, particularly for large or specialized catalogs within Brightcove's ecosystem. As platforms scale video offerings, robust metadata management becomes critical for both internal workflows and end-user search experiences. Moving forward, observe how this increased customization impacts search accuracy and content segmentation across Brightcove-powered platforms.

This update on custom metadata fields builds on Brightcove's recent focus on enhancing content management and discoverability. In late 2025, Brightcove introduced its Metadata Optimizer, an AI-powered assistant designed to auto-generate video metadata, including titles, descriptions, and tags (per Brightcove's blog, October 2025). This AI tool is integrated into Video Cloud Studio and aims to streamline workflows by providing smart suggestions for metadata, reducing manual tagging effort. The Metadata Optimizer leverages text tracks, audio, and visual analysis, with an advanced option for deeper analysis. It supports over 40 languages and allows for multi-language metadata generation. Users can review and approve AI suggestions in the Media module or integrate the functionality via API, and can also define custom tag rules to align generated metadata with specific organizational taxonomies (per Brightcove support documentation). The current detailed documentation for custom metadata fields offers the framework for structuring the data that these AI tools can populate, further empowering publishers to maintain consistent and searchable libraries.