Scale your content moderation with accurate AI detection. Identify AI-generated spam, fake reviews, and synthetic content before it undermines your platform's integrity and user trust.
AI-generated content creates new challenges for platform integrity that traditional moderation tools were not designed to handle.
Emerging regulations around AI-generated content and transparency are creating new compliance requirements. Proactively detecting synthetic content helps your platform stay ahead of regulatory expectations.
AI-generated fake reviews, spam comments, and synthetic profiles erode the quality of your platform. Detection helps you identify and act on inauthentic content at scale.
Your users expect authentic interactions. When AI-generated content proliferates unchecked, user trust and engagement decline. Detection is a critical tool for maintaining a healthy platform ecosystem.
Bad actors use AI to generate disinformation, phishing content, and social engineering attacks at scale. AI detection adds a layer of defense against coordinated inauthentic behavior.
Detection capabilities built for the demands of production content moderation systems.
Automated AI detection costs a fraction of manual review. Use detection as a first pass to prioritize content that needs human moderator attention, reducing review costs significantly.
Our models are optimized for the types of content common on platforms: reviews, comments, bios, and posts. While longer texts yield more reliable results, we provide useful signals even on shorter content.
Our models are trained and benchmarked on English prose, and we make no accuracy claims for other languages. If your platform handles multiple languages, our checker should only be pointed at the English content.
Every detection result includes a confidence score and a clear verdict. Set your own thresholds to auto-moderate high-confidence detections while routing borderline cases to human reviewers.
Our ensemble of detection algorithms provides more robust results than any single model. Cross-referencing multiple signals reduces both false positives and false negatives.
Analysis typically completes in seconds, enabling near-real-time moderation workflows. Content can be screened as it is submitted without noticeable delays to your users.
Flexible integration paths designed for engineering teams building moderation pipelines.
A straightforward REST API that accepts text and returns structured detection results including verdict, confidence score, and sentence-level analysis. Easy to integrate into any moderation pipeline.
Bulk screening is available as a custom integration with your moderation pipeline. Ideal for backfill operations, periodic audits, or working through queues of flagged content.
Integrate detection into your content submission flow for real-time screening. Low latency responses allow you to flag or hold content before it becomes visible to other users.
API responses include machine-readable verdicts, confidence scores, and per-sentence breakdowns. Feed results directly into your moderation queue, rules engine, or analytics pipeline.
Integrate AIDetector.review into your moderation pipeline. Our API provides structured detection results with confidence scores, enabling automated screening at production scale.
Free to try. Custom integrations for high-volume teams.