Kazan SEO AI Detector
Professional-grade AI content detection and semantic SEO analysis at zero cost.
Enterprise-grade linguistic forensics for verifiable human authenticity in the age of generative AI.
ContentGuard AI Detector represents a sophisticated evolution in linguistic analysis, specifically engineered for the 2026 landscape where synthetic and human-authored content are deeply converged. The platform utilizes a multi-vector detection engine that moves beyond simple perplexity and burstiness metrics. It integrates semantic entropy analysis, structural fingerprinting, and model-specific marker identification to distinguish between human creativity and LLM-generated output from models like GPT-5, Claude 4, and Llama 4. Positioned as a mission-critical tool for publishers, educational institutions, and legal firms, ContentGuard provides a 'Forensic Heatmap' that pinpoints specific passages likely to be synthetic. Its architecture is built on a proprietary transformer-based classifier that is continuously fine-tuned on diverse datasets, including human-AI collaborative writing, to minimize false positives. In the 2026 market, ContentGuard differentiates itself through its 'Source Attribution' feature, which not only flags AI presence but identifies the probable model family used. The platform supports batch processing of massive document repositories and offers a seamless API for real-time content moderation, making it a cornerstone for organizations maintaining high-trust information environments.
Identifies the specific LLM architecture (e.g., GPT series, Claude, Gemini) by analyzing structural patterns and specific tokens.
Professional-grade AI content detection and semantic SEO analysis at zero cost.
Forensic-level AI content detection and advanced humanization for SEO-proof content.
Transform AI-generated text into undetectable, human-grade content with advanced linguistic humanization.
A non-profit open-source detector for educational integrity and transparent AI verification.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Provides a sentence-level visualization of AI probability using gradient shading.
Uses computer vision to extract text from screenshots or scanned documents for AI analysis.
Tracks changes in a writer's style over time to detect sudden shifts to AI-assisted output.
Calculates the unpredictability of word choice compared to standardized LLM weightings.
Checks document metadata for traces of AI-tool usage (e.g., hidden tags or timestamps).
Detection engine updated weekly to counter 'humanizing' tools and prompt engineering bypasses.
Ensuring student submissions are original work in an era of advanced LLMs.
Registry Updated:2/7/2026
Preventing search engine penalties for mass-produced AI content.
Confirming that paid freelancers are providing human-written value.