Word Counter AI Detector
Professional-grade AI content verification integrated with world-class word counting metrics.
Advanced linguistic forensics to differentiate between human creativity and algorithmic output.
AI Detector by SEOToolGarage is a high-precision linguistic analysis tool designed to identify the probabilistic fingerprints left by Large Language Models (LLMs) such as GPT-4, Claude 3.5, and Gemini. By 2026, the tool has matured into a sophisticated forensic engine that evaluates text based on 'Perplexity' (predictability of words) and 'Burstiness' (variance in sentence structure). Unlike basic pattern matchers, SEOToolGarage's architecture utilizes a multi-layer verification process that scans for the uniform distribution of vocabulary typical of machine-generated content. In the 2026 market landscape, where AI-generated content is the norm, this tool positions itself as a critical 'sanity check' for SEO agencies, academic institutions, and publishers who prioritize E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness). The platform provides a granular heatmap visualization, highlighting specific segments of text that exhibit high-probability machine characteristics. While many enterprise detectors have moved behind significant paywalls, SEOToolGarage maintains a high-utility free-to-use model, making it an essential utility for independent creators and small-to-medium-sized digital marketing teams who require rapid, reliable validation without heavy overhead.
Measures the entropy of the text; lower perplexity indicates higher predictability characteristic of LLMs.
Professional-grade AI content verification integrated with world-class word counting metrics.
Enterprise-grade linguistic analysis for identifying LLM-generated content across multi-model architectures.
Professional-grade linguistic analysis to distinguish between human-authored and LLM-generated content with high-granularity scoring.
Enterprise-grade forensic engine for high-precision AI content verification and linguistic integrity.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Analyzes the variance in sentence length and structure across the document.
Color-coded overlay highlighting segments with high AI-probability scores.
Algorithms trained on datasets from OpenAI, Anthropic, Google, and Meta.
Evaluates text against known 'robotic' transition phrases and common AI filler patterns.
Ensures processed text is not used for further model training or stored permanently.
Cross-references writing style across the entire document to detect 'Hybrid' AI-human writing.
Ensuring student submissions are original works rather than LLM outputs.
Registry Updated:2/7/2026
Avoiding search engine penalties for low-effort, bulk AI-generated content.
Publishers verifying that external contributors are providing unique, human-written content.