Image Moderation

Overview

SafetyKit's image moderation uses advanced visual AI to identify explicit content, violence, and brand safety risks in user-uploaded images. Our models analyze visual elements, embedded text, and contextual signals to provide accurate moderation decisions at scale.

Key Capabilities

• Multi-signal analysis: Combines visual recognition, OCR, and contextual understanding
• Granular classification: Detailed categorization beyond binary safe/unsafe decisions
• Custom thresholds: Configure sensitivity levels for different content categories
• Batch processing: Review historical image libraries for compliance

Detection Categories

How It Works

Visual Analysis Pipeline

1. Object Detection: Identify objects, people, and scene elements
2. Content Classification: Categorize content across safety dimensions
3. Text Extraction: OCR processing for embedded text analysis
4. Enforcement Decisions: Makes enforcement decisions automatically, with configurable thresholds for routing edge cases to human review

Integration Options

• Direct image URL analysis
• Base64 encoded image upload
• Cloud storage integration (S3, GCS, Azure Blob)
• Webhook callbacks for asynchronous processing

Use Cases

Performance at Scale

SafetyKit's image moderation processes millions of requests daily with consistent accuracy. Our models are continuously updated to address emerging abuse patterns without requiring manual rule updates.

Performance

Coverage

Agility

Related Capabilities

• Text Moderation
• Video Moderation
• Audio Moderation
• AI-Generated Content Detection