Zefr for Facebook
In-Stream Video

GARM Standard Brand Safety & Suitability

Human-supervised machine learning powers Zefr Allow Lists which constantly update to avoid universally sensitive videos as defined by GARM and the Advertiser Protection Bureau, keeping brands ahead of shifting safety trends and simplifying workflows.

Dynamic Content & Page Level Decisioning

Dynamically filter out specific content deemed unsuitable for your brand globally with 5-minute refreshes, to minimize wasted impressions at the video-level that arise from broad page/publisher-level inclusion lists.

The Zefr Difference on Facebook

Global Support

Activate across 20+ languages.

Optimized for Scale.

Dynamic refreshes rather than daily updates.

Architected for Video.

Human-in-the-loop architecture goes beyond the metadata.

Ready to learn more about Zefr’s unique data approach to video suitability?