Protect your social community with enterprise-grade AI moderation. Detect hate speech, harassment, NSFW content, misinformation, and coordinated abuse across posts, comments, stories, reels, and DMs with 99.9% accuracy and sub-50ms latency.
Social media platforms generate staggering volumes of user-generated content every second. From text posts and photos to videos, stories, reels, and live streams, every piece of content needs analysis before it reaches your audience. Our AI-powered moderation API processes content at the speed your platform demands.
Analyze text posts, comments, replies, and threads in real time. Detect hate speech, harassment, bullying, spam, and policy violations with contextual understanding that accounts for sarcasm, coded language, and cultural nuance across 100+ languages.
Scan ephemeral content including stories, reels, and short-form videos for NSFW imagery, violent content, policy violations, and harmful overlays. Frame-by-frame video analysis catches violations that static image scanning misses entirely.
Protect users in private messaging with on-device or server-side scanning that detects predatory behavior, sextortion, grooming patterns, unsolicited explicit images, and scam links while preserving end-to-end privacy expectations.
Identify automated accounts, bot networks, and coordinated inauthentic behavior through behavioral fingerprinting, posting pattern analysis, and network graph detection. Stop astroturfing and spam farms before they pollute your platform.
Detect and label false claims, manipulated media, and viral misinformation campaigns using claim verification, source credibility scoring, and deepfake detection. Integrate with third-party fact-checkers for comprehensive coverage.
Uncover organized brigading, pile-on attacks, and targeted harassment campaigns through network analysis. Identify accounts working in concert to overwhelm, silence, or intimidate specific users or communities.
Social media content arrives in dozens of formats, and each requires specialized analysis. Our multi-modal AI engine classifies and routes content to the appropriate detection models automatically, ensuring maximum accuracy for every content type.
Text posts are analyzed for toxicity, sentiment, and policy violations. Images pass through NSFW detection, OCR for embedded text, and object recognition. Videos receive frame-level analysis combined with audio transcription. Stories and reels trigger ephemeral content pipelines optimized for speed.
Modern social media harassment rarely comes from a single account. Coordinated campaigns involve dozens or hundreds of accounts working together to target individuals and communities. Traditional per-post moderation misses the bigger picture entirely.
Our network graph analysis maps relationships between accounts, identifies clusters of coordinated behavior, and detects brigading campaigns before they reach critical mass. The system tracks interaction patterns, timing correlations, and content similarity to surface organized attacks that would otherwise appear as independent actions.
Not every moderation decision is clear-cut. Ambiguous content needs human review, and users deserve fair appeal processes. Our moderation queue system intelligently prioritizes content for review based on severity, confidence scores, and potential impact, ensuring your human moderators focus on the cases that matter most.
The appeal workflow engine automates the end-to-end process from initial user appeal through secondary AI review, human escalation, and final resolution. Transparent decision logging ensures compliance with DSA, NetzDG, and emerging platform accountability regulations worldwide.
Platform safety is not just about removing bad content. It is about understanding the overall health of your community and making data-driven decisions to improve it. Our analytics dashboard provides real-time visibility into content trends, moderation effectiveness, and community sentiment.
Track toxicity scores over time, monitor the ratio of flagged content to total volume, measure moderator efficiency, and identify emerging threats before they go viral. Customizable alerts notify your trust and safety team when community health metrics deviate from baselines.
Every social media platform defines its own community guidelines, but enforcing them consistently across billions of interactions is an extraordinary challenge. What constitutes acceptable speech varies by context: a comment that is fine in a comedy community may violate guidelines in a parenting group. Our AI moderation engine lets you define granular, context-aware policies that adapt to your platform's unique standards while maintaining overall consistency.
The policy engine supports hierarchical rule sets where platform-wide rules form the baseline, and community-specific or region-specific rules add additional constraints or relaxations. Rules can be expressed in natural language and are compiled into optimized detection models that evaluate content in milliseconds. When guidelines change, updated rules deploy across the entire moderation pipeline within minutes, not weeks.
Automated enforcement actions range from soft interventions like content warnings and reduced distribution to hard interventions like removal, account suspension, and law enforcement referral. The severity of the action matches the severity of the violation, and every decision is logged for transparency and appeals.
Outright removal is not always the best response. For borderline content, misinformation, or potentially misleading posts, applying informational labels preserves user expression while adding critical context. Our content labeling system attaches machine-readable and human-readable labels to flagged content, enabling your platform to display warnings, link to authoritative sources, or reduce algorithmic amplification without full removal.
Labels include categories such as misinformation, satire, sensitive content, unverified claims, graphic content, and sponsored material. Each label carries a confidence score and supporting evidence that your platform can use to determine the appropriate user-facing treatment. For political content and news articles, the system cross-references claims against fact-check databases and provides source credibility ratings.
Attach fact-check context to viral claims. Cross-reference with 50+ fact-checking organizations worldwide. Display source credibility ratings alongside shared links.
Apply interstitial warnings to graphic, disturbing, or potentially triggering content without removing it. Users opt-in to view with a single tap.
Automatically classify content by age-appropriateness. Enforce age-gating for alcohol, tobacco, gambling, and mature-themed content. Integrate with platform age verification systems.
Ensure ads never appear alongside harmful, controversial, or off-brand content. Real-time adjacency scoring keeps advertisers safe and revenue protected.
Protecting younger users is a non-negotiable responsibility for social media platforms. Regulatory bodies worldwide are imposing stricter requirements around child safety, from COPPA in the United States to the UK Age-Appropriate Design Code and the EU Digital Services Act's enhanced protections for minors. Our age-gating system provides a multi-layered approach to minor protection that goes far beyond simple birthday checks.
The system classifies content against age-tier thresholds (13+, 16+, 18+) and restricts visibility accordingly. It detects grooming language patterns in direct messages, identifies age-inappropriate content in feeds targeting younger demographics, and flags potential predatory behavior through behavioral analysis. Integration with your platform's age verification system ensures that age-restricted content reaches only verified adult audiences.
For platforms with mixed-age audiences, the AI dynamically adjusts feed content to match the user's age tier. Content creators receive clear guidance when their uploads trigger age restrictions, and the appeals process provides educational context about what specific elements caused the restriction.
Content creators are the lifeblood of social media platforms, and their safety directly impacts platform health, creator retention, and content quality. Creators face unique threats including targeted harassment campaigns, doxxing, swatting, impersonation, and copyright theft. Our creator safety toolkit provides specialized protections that shield creators from these threats while preserving authentic fan engagement.
Comment filtering allows creators to define custom keyword lists, toxicity thresholds, and account-age minimums for comments on their content. Harassment shields detect when a creator is being targeted by a surge of negative engagement and automatically increase moderation sensitivity, hold suspicious comments for review, and alert the creator with a digest rather than exposing them to each individual attack. Impersonation detection identifies accounts mimicking a creator's name, profile picture, or content style and flags them for rapid takedown.
For live streaming, real-time chat moderation filters toxic messages, detects raid attacks, and provides creators with one-click tools to slow chat, restrict to followers-only, or activate emergency lockdown modes. These tools empower creators to manage their own communities while platform-level protections handle the threats they cannot see.
Advertising revenue drives social media platforms, and brand safety incidents can destroy advertiser trust overnight. A single screenshot of a major brand's ad appearing next to extremist content or graphic violence can trigger an ad boycott that costs millions. Our brand safety system ensures that ads are never served alongside content that violates advertiser preferences.
The system operates on two levels. Pre-placement scoring evaluates content before ad slots are assigned, ensuring that only brand-safe pages receive premium advertising inventory. Real-time adjacency monitoring continuously checks the content surrounding active ad placements and triggers instant re-routing if the context changes, such as when a previously safe comment section becomes toxic during a viral moment.
Advertisers can define custom brand safety profiles with category-level exclusions (violence, adult content, political controversy, profanity) and granular topic-level controls. The API returns brand safety scores and category tags for every piece of content, enabling your ad-serving platform to make intelligent placement decisions in real time. Detailed reporting shows advertisers exactly how their brand safety requirements were enforced.
Human moderation teams are essential for handling nuanced edge cases and appeals, but they cannot scale linearly with content volume. Doubling your user base should not mean doubling your moderation headcount. Our AI moderation API handles the high-volume, clear-cut decisions automatically, reducing human review queues by 85% or more while maintaining accuracy levels that match or exceed human moderators for standard violation categories.
The confidence-based routing system sends only genuinely ambiguous content to human reviewers. High-confidence violations are actioned automatically. High-confidence safe content passes through without delay. The gray zone in between is prioritized by potential harm severity, with child safety and imminent threats at the top of every queue. This approach lets your human team focus their expertise where it matters most, improving both moderator wellbeing and decision quality.
Auto-scaling infrastructure handles traffic spikes during viral events, breaking news, and product launches without performance degradation. Geographic edge distribution across 50+ locations ensures sub-50ms response times for users worldwide. The result is consistent, reliable moderation at any scale, from a startup social app with thousands of users to a global platform with billions.
Common questions about content moderation for social media platforms.
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