EX.CO’s Agentic AI Taxonomy Solution Empowers Publishers to Transform Video Archives into Revenue-Ready Assets

Now live across Ziff Davis properties, new solution organizes video libraries with intelligent categorization, eliminates manual tagging, and enhances searchability and monetization
EX.CO, the machine learning video technology platform powering successful video strategies for the world’s leading media groups, announced the launch of a powerful new agentic AI taxonomy feature, now live across Ziff Davis properties. This breakthrough solution enables publishers to automatically categorize their video content using a blend of proprietary and industry-standard classification models—turning disorganized archives into structured, searchable, and monetizable assets in real time.
“EX.CO’s AI taxonomy solution has allowed us to deeply tag our extensive video library with a fraction of the necessary time. This gives the product team confidence in the recommendations being powered by this new technology,” said Dan Kamas, senior product manager at Ziff Davis.
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Unlike legacy systems that rely on time-consuming manual tagging, EX.CO’s taxonomy solution uses Large Language Models (LLMs) to analyze video content frame by frame—generating rich metadata across more than 30 dimensions, including IAB categories, sentiment, tone, safety classification, and contextual relevance. These intelligent categories make it significantly easier to match video content with appropriate advertising demand, improving both targeting precision and yield.
The system also offers full support for publishers with existing custom taxonomies, allowing seamless integration between new, AI-powered classification and longstanding editorial structures. Whether starting from scratch or enhancing an existing framework, EX.CO’s flexible architecture ensures an easy path to adopting LLM and agentic AI technologies—without sacrificing control. What sets EX.CO’s solution apart from broader contextual platforms is its ability to complement, not replace, existing editorial taxonomies—bridging legacy systems with next-gen automation, and translating that structure into real monetization opportunities.
“What makes this solution different isn’t just automation—it’s precision and adaptability,” said Tom Pachys, co-founder and CEO at EX.CO. “We’re leveraging LLM models to recreate the publisher’s unique content hierarchy, evolve alongside editorial strategies, and integrate directly into existing CMS and monetization workflows. It’s not just smart tagging—this is foundational infrastructure for scalable, context-aware video.”
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Already live across Ziff Davis properties including PCMag and Mashable, EX.CO’s AI-driven taxonomy solution enables:

Seamless content alignment to keep video and article content in sync
Improved search and discovery, making internal content retrieval and matching on both the EX.CO platform and publisher CMS more efficient
Custom category frameworks with configurable confidence thresholds
Smarter curation and monetization via enriched metadata for contextual targeting, better audience targeting, and bid optimization
Instant SEO enrichment by embedding relevant taxonomy directly into video metadata

“We can now tag our vast content library with depth and confidence in a fraction of the time, thanks to this product,” said Dan Kamas, Senior Product Manager at Ziff Davis.
The feature is currently available to EX.CO publisher partners with AI-powered analysis enabled. It offers end-to-end tagging at a fraction of the cost required for manual execution and ongoing maintenance—making it a highly efficient and scalable solution.
“Our new agentic AI taxonomy feature doesn’t just drive revenue—it deepens our value with editorial and video stakeholders who depend on speed and accuracy to do their jobs well,” added Pachys. “We have a responsibility to bring the latest technologies (and specifically AI) to our publishers, and are thankful to have partners that work with us to help shape the future. ”

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