AI Content Detector — Free Text Analysis
Analyze text for AI-generated patterns using perplexity, burstiness, and vocabulary diversity. Free, private — runs entirely in your browser.
About AI Content Detector
This tool uses statistical analysis to identify patterns commonly associated with AI-generated text. It measures perplexity (how predictable the word choices are), burstiness (variation in sentence length), vocabulary diversity, and repetition patterns.
Important: This is a statistical analyzer, not a definitive AI detector. Results indicate statistical patterns only. Human writing can show AI-like patterns, and AI-generated text can mimic human patterns. Use this as one data point among many.
Statistical detection methods measure properties like perplexity — how surprised a language model is by each word choice. AI-generated text typically has lower perplexity because language models select statistically likely words. Human writing tends toward higher perplexity because people choose unexpected words, use idioms, and make deliberate stylistic choices.
Detection accuracy has inherent limitations. Lightly edited AI text often evades detection, while formulaic human writing (legal documents, technical manuals, press releases) frequently triggers false positives. No detection tool should be used as the sole basis for academic integrity decisions or content policy enforcement.
This analyzer provides raw statistical metrics rather than a binary AI-or-human verdict. You see the actual perplexity distribution, burstiness score, vocabulary diversity ratio, and repetition patterns. This transparency lets you form your own judgment rather than relying on an opaque confidence percentage. Use it alongside the AI Text Analyzer for the most comprehensive view.
How the AI Content Detector Works
- Paste the text you want to analyze
- The tool examines patterns like perplexity, burstiness, and vocabulary distribution
- See a confidence score indicating the likelihood of AI-generated content
- Review highlighted sections that triggered detection signals
Limitations of AI Content Detection
AI detection tools analyze statistical patterns in text — AI-generated text tends to have lower perplexity (more predictable word choices) and lower burstiness (more uniform sentence length). However, no detector is 100% accurate: false positives flag human text as AI, and lightly edited AI text often evades detection. These tools are best used as one signal among many, not as definitive proof. Academic and professional standards for AI use vary widely.
When to Use the AI Content Detector
Use this tool when you need a preliminary statistical analysis of text patterns that may indicate AI generation. It is useful as one input among many when reviewing submitted content, but should never be used as the sole basis for accusations or decisions. Academic and editorial contexts benefit most from the transparency of seeing raw metrics rather than an opaque verdict.
Common Use Cases
- •Getting a statistical overview of text patterns in submitted content
- •Comparing the statistical profiles of known AI-generated and human-written samples AI Text Analyzer — Pattern & Style Metrics
- •Evaluating your own AI-assisted writing to ensure it reads naturally
- •Analyzing text burstiness and perplexity for linguistic research
Expert Tips
- ✱Analyze at least 300 words for meaningful results — shorter samples produce unreliable statistical measurements.
- ✱Compare the metrics against known samples of the author's writing style before drawing conclusions.
- ✱Low burstiness alone does not prove AI authorship — technical manuals and legal documents naturally have uniform sentence lengths.
Frequently Asked Questions
- No AI detector is fully reliable. Studies show false positive rates of 5-15% (human text flagged as AI) and false negative rates of 10-30% (AI text passing as human). Lightly edited AI text, translated text, and formulaic writing (legal, medical, technical) are particularly prone to misclassification. Use results as one data point, not a definitive judgment.
- Perplexity measures how predictable each word is given the preceding context. Low perplexity means the words are statistically expected — a pattern common in AI-generated text. High perplexity means unexpected word choices, which is more common in human writing. However, well-edited professional writing can also show low perplexity.
- Yes, with relatively simple editing. Paraphrasing, adding personal anecdotes, varying sentence structure, and introducing deliberate stylistic choices can shift statistical metrics toward human-like patterns. This is one reason why statistical detection should not be used as the sole basis for content policy enforcement.
- No. This tool uses purely statistical analysis — mathematical measurements of text properties like word frequency distribution, sentence length variation, and vocabulary diversity. It does not send your text to any AI model or external API. All calculations happen locally in your browser.
How accurate is AI content detection?▾
What does perplexity measure?▾
Can AI text be made undetectable?▾
Does this tool use AI to detect AI?▾
Related Tools
AI Token Counter — GPT, Claude & Gemini
Count tokens for GPT, Claude, Gemini, and other AI models. Estimate costs per API call with built-in pricing. Free online tool.
AI Model Comparison — 50+ Models Side by Side
Compare 50+ AI models: pricing, context windows, capabilities, and benchmarks. Filter by provider, open source, and features.
AI Text Analyzer — Pattern & Style Metrics
Analyze text patterns: sentence variation, vocabulary diversity, repetition, and burstiness scores. Free writing analysis tool.
AI Prompt Generator — Structured Builder
Build structured prompts for ChatGPT, Claude, and other AI models. Select role, task, context, and format. Free prompt engineering tool.
AI Image Prompt Builder — Midjourney & More
Build prompts for Midjourney, DALL-E, Stable Diffusion, and Flux. Style, lighting, and composition controls. Free prompt tool.
System Prompt Builder — AI Instructions
Build structured system prompts for ChatGPT, Claude, and other AI models. Model-specific export formats. Free prompt builder.
Learn More
AI Tools Every Developer Should Know in 2026: Tokens, Prompts, and Model Selection
A practical guide to AI development tools: understanding tokens, writing effective prompts, comparing models, and optimizing costs for LLM-powered applications.
AI Content Detection & Analysis: How to Verify, Analyze, and Improve AI-Generated Text
Learn how to detect AI-generated content, analyze text quality, and use AI writing tools responsibly. Covers content detection, text analysis, readability checking, and prompt engineering.