Detect Spam With AI. Not Rules.

ActiveLayer runs every submission through multiple AI models in parallel. Content pattern analysis evaluates the text for promotional language, obfuscated links, and social engineering patterns. Linguistic analysis detects spam phrasing and AI-generated content. Sender reputation checks the email address and IP against a database built from millions of checks. Behavioral analysis identifies automated submission patterns and campaign signals. All signals combine into a single verdict with confidence score and signal breakdown. The entire process takes under 100ms.

99.5%+ detection accuracy across all signal types. Every verdict includes the confidence score and detection signals, so you can verify decisions yourself. The feedback loop lets you correct any mistakes, and the AI incorporates your corrections into future verdicts. Accuracy improves over time for your specific use case.

Two ways. First, confidence scores let you set custom thresholds. Instead of auto-blocking everything flagged as spam, you can route medium-confidence submissions (0.6 to 0.9) to a review queue and only auto-block high-confidence spam (above 0.9). Second, the feedback endpoint lets you report false positives with the detection ID. The AI learns from your corrections and reduces future false positives for your specific content patterns.

Yes. On two levels. Network-wide: the AI models are retrained continuously on new spam data from across the entire ActiveLayer network. When a new spam technique appears anywhere, detection updates propagate to all protected sites. Per-site: the feedback loop lets you submit corrections that tune detection for your specific content patterns and audience. Both happen automatically. You never update a rule or configure a filter.

Yes. AI-generated spam is one of the fastest-growing threats, and it’s specifically what ActiveLayer’s content analysis models are trained to catch. The AI evaluates linguistic patterns, content structure, and contextual signals that distinguish AI-generated spam from legitimate human submissions. As AI-generated spam techniques evolve, ActiveLayer’s models are retrained to keep detection current.

Yes. ActiveLayer’s AI models detect spam patterns across languages. The content analysis is not limited to English. Linguistic signals, promotional patterns, and obfuscated link detection work regardless of the submission language. The reputation and behavioral signal layers are language-agnostic by nature.

Yes. The feedback endpoint (POST /api/v1/feedback) lets you report false positives and false negatives with the detection ID. The AI incorporates your corrections and improves detection for your specific content patterns over time. This is especially valuable for platforms with niche or specialized content where general-purpose models might over-flag legitimate submissions. Available on all plans. No additional setup required.

Basic ML spam filters typically analyze a single signal type, often just content. They miss multi-vector attacks where the content looks clean but the sender is a known spammer, or where the behavioral pattern is automated but the text is AI-generated. ActiveLayer combines 6+ signal types in parallel: content patterns, linguistic analysis, sender reputation, IP intelligence, email pattern detection, and behavioral indicators. The result is higher accuracy, fewer false positives, and detection that adapts to new tactics without manual configuration.