Brand Safety Verification
Automate brand safety verification for ad placements, influencer partnerships, and content syndication. Score content against GARM categories and custom brand guidelines using Mixpeek multimodal analysis.
Brand safety teams at agencies, DSPs, SSPs, ad networks, and brand marketers who need to verify that ad placements and content partnerships meet safety standards before spend is allocated
Brand safety violations in ad placements damage brand reputation, trigger advertiser boycotts, and waste media spend. Manual review cannot scale to the volume of content environments where ads appear. Existing tools check text context only, missing unsafe visual and audio content in video placements.
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Before & After Mixpeek
Before
Brand safety method
Keyword blocklists and text-only context analysis
Video placement safety
Metadata-only checks, visual content unverified
Custom brand rules
Manual review for direct deals, no automation
After
Brand safety method
Multimodal GARM scoring across text, image, video, and audio
Video placement safety
Frame-level visual analysis with audio classification
Custom brand rules
Automated scoring against brand-specific taxonomies
Brand safety violation exposure
95% reduction
Safe inventory reach
+20% reach
Verification latency
Real-time
Why Mixpeek
Multimodal analysis catches brand safety violations that text-only tools miss entirely. A video with benign metadata but violent visual content, or an article with safe headlines but explicit embedded images, fails multimodal analysis while passing traditional keyword-based safety checks. Mixpeek delivers GARM-compliant scoring with sub-100ms API latency for programmatic integration.
Overview
Brand safety verification protects advertisers from appearing alongside content that conflicts with their brand values, triggers consumer backlash, or violates regulatory standards. The challenge is scale: programmatic advertising places ads across millions of content environments, and manual review is impossible at that velocity. Mixpeek automates brand safety verification by analyzing content environments through multimodal AI. Every piece of content is scored against standardized safety frameworks (GARM categories) and custom brand-specific rules. Scores feed directly into bidding infrastructure for real-time pre-bid filtering, or into dashboards for content partnership evaluation. The multimodal approach is critical because brand safety violations increasingly exist in visual and audio content that text-based tools cannot detect. A news article about a natural disaster might have safe body text but graphic images. A podcast might have benign show notes but explicit audio content. A video might pass keyword checks but contain violent scenes. Mixpeek analyzes all modalities together, providing comprehensive safety scoring that reflects the actual content a consumer would experience alongside the ad placement. The pipeline integrates at multiple points in the advertising workflow: pre-bid filtering in programmatic buying, content vetting for direct deals and sponsorships, ongoing monitoring of placement quality, and retrospective analysis for brand safety reporting. Feature extractors process visual frames, audio segments, and text content. Collections organize detection models by safety framework. Retrievers enable search across scored inventory to discover safe placement opportunities and monitor for emerging risks.
Challenges This Solves
Volume Beyond Human Review
Programmatic advertising evaluates millions of placement opportunities per day, far exceeding human review capacity
Impact: Without automated verification, brands rely on blocklists that are always incomplete and exclude safe inventory, wasting 10-20% of potential reach.
Multimodal Blind Spots
Text-based brand safety tools analyze page context and metadata but cannot evaluate visual or audio content in video placements
Impact: Brand safety violations in CTV, social video, and multimedia content go undetected, exposing brands to adjacency risk in the fastest-growing ad formats.
Custom Brand Guidelines
Each brand has unique safety requirements beyond standard GARM categories, including competitor adjacency, political sensitivity, and category-specific rules
Impact: One-size-fits-all safety tools force brands into overly broad blocking that sacrifices reach, or overly permissive settings that allow violations.
Recipe Composition
This use case is composed of the following recipes, connected as a pipeline.
Feature Extractors Used
brand safety violence
brand safety hate speech
brand safety adult content
Scene Classification
Categorize images based on scene type (indoor, outdoor, etc.)
Object Detection
Identify and locate objects within images with bounding boxes
ocr text extraction
+1 more extractors
Retriever Stages Used
semantic search
filter aggregate
Expected Outcomes
95% reduction in unsafe ad adjacency
Brand safety violation rate
+20% more placements by replacing blocklists with precision scoring
Safe inventory reach
Sub-100ms API response for real-time pre-bid integration
Verification speed
100% of video placements verified versus metadata-only baseline
CTV and video coverage
Automate Brand Safety Scoring
Clone the brand safety verification pipeline and integrate multimodal GARM scoring into your ad operations.
Frequently Asked Questions
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Ready to Implement This Use Case?
Our team can help you get started with Brand Safety Verification in your organization.