How do you handle false positives?

We implement confidence thresholds — content above 95% confidence is auto-actioned, content between 60-95% goes to human review, and content below 60% is allowed. Users can appeal any decision through a structured review process.

Can the system handle multiple languages?

Yes. We use multilingual AI models that support 50+ languages. Cultural context and language-specific slurs are handled through custom dictionaries and regional policy rules.

What about video content moderation?

We sample video frames for image analysis and transcribe audio for text analysis. For real-time streams, we use frame sampling at configurable intervals.

Content Moderation That Protects Your Platform

AI-powered text analysis, image scanning, and human review queues. Our AI-managed teams build content moderation systems that keep your community safe at scale.

Solution: Content Moderation

Content moderation systems protect platforms from harmful, illegal, and policy-violating content. Production systems combine AI classification for speed with human review for accuracy, handling text, images, video, and user profiles. The challenge is maintaining safety while minimizing false positives and preserving the user experience.

Stack Components

OpenAI Moderation / Perspective API (Text Classification): AI models that classify text for toxicity, hate speech, harassment, and custom policy categories with confidence scores.
AWS Rekognition / Google Vision (Image Moderation): Computer vision APIs that detect explicit content, violence, and policy-violating imagery in user-uploaded images.
React / Next.js (Review Dashboard): Moderator dashboard with review queues, decision tools, appeal management, and performance analytics.
PostgreSQL / Redis (Decision Storage): Stores moderation decisions, appeal history, user trust scores, and action logs with fast queue processing.
Kafka / SQS (Content Queue): Message queue for processing content submissions asynchronously with priority-based routing to human reviewers.

Best For

Social media and community platforms
User-generated content marketplaces
Dating and matchmaking apps
Forum and discussion platforms
E-commerce product listings and reviews
Educational platform submissions

Case Studies

Community Platform Moderation: AI-powered moderation system for a community platform with 500K+ posts monthly, combining automated filtering with human review queues.
- AI catches 92% of policy violations automatically
- Human review queue for borderline content with 4-hour SLA
- Appeal workflow with second-reviewer escalation
- False positive rate under 3%
Marketplace Listing Review: Automated screening of product listings for prohibited items, misleading descriptions, and IP violations on an e-commerce marketplace.
- Image scanning for counterfeit and prohibited products
- Text analysis catching misleading health and safety claims
- Seller trust scoring based on moderation history

Frequently Asked Questions

How do you handle false positives?: We implement confidence thresholds — content above 95% confidence is auto-actioned, content between 60-95% goes to human review, and content below 60% is allowed. Users can appeal any decision through a structured review process.
Can the system handle multiple languages?: Yes. We use multilingual AI models that support 50+ languages. Cultural context and language-specific slurs are handled through custom dictionaries and regional policy rules.
What about video content moderation?: We sample video frames for image analysis and transcribe audio for text analysis. For real-time streams, we use frame sampling at configurable intervals.