Asset Finder for Articles

How does it work?

Asset Finder for Articles handles the visual research that slows down publication. Ask questions like:

• Find images that match this article about renewable energy trends?
• What product photos do we have for the new software launch?
• Show me lifestyle images featuring remote work?
• What videos do we have related to customer success stories?
• Find infographics about supply chain logistics?
• What assets did we use for last quarter's sustainability campaign?
• Are there any approved headshots of our leadership team?

The Assistant searches your DAM and file repositories, analyzes metadata and keywords, and delivers a ranked list of options—complete with source links and usage details—so you can attach the right asset in seconds.

Who uses Asset Finder for Articles?

Asset Finder for Articles is built for content teams who need the right visuals without the search time:

• Editors selecting images and media to accompany articles before publication
• Content Marketers matching assets to campaigns and blog posts
• Social Media Managers finding approved visuals for cross-channel promotion
• Creative Directors ensuring brand-consistent imagery across publications

It's especially valuable for teams managing high-volume content calendars—where manually hunting through asset libraries for every article slows down the entire editorial workflow.

How does Asset Finder for Articles use your Knowledge Base?

Asset Finder for Articles searches across your connected DAM systems, asset repositories, and file storage to surface the most relevant images, videos, and files for your content.

• Analyzes your article's topics, keywords, and context
• Queries asset repositories using metadata, tags, and descriptions
• Returns a ranked list of recommended assets based on relevance
• Provides source links, usage rights, and file details for each recommendation

Because the Knowledge Base syncs continuously with your asset sources, you're always seeing the latest approved media—not outdated files or assets that have been archived.