Free AI Content Detector

Analyze text for AI-generated patterns using 7 statistical signals. Private, instant, no signup required.

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Paste text to analyze

This tool analyzes 7 statistical signals to detect AI-generated text. Minimum 50 words, 200+ recommended.

Pro Tips

1.

Longer is better: 50 words is the minimum, but 200+ words gives significantly more reliable results across all 7 signals.

2.

Test multiple sections: AI-generated articles often vary in detectability. Test the introduction, middle, and conclusion separately.

3.

Look at the signals, not just the score: A high burstiness score alone might mean a formal style, but high burstiness combined with high AI phrase density is a stronger signal.

4.

Edited AI text is harder to detect: If someone generates AI text and then edits it, the statistical patterns change. A 'mixed' result may indicate edited AI content.

5.

Check the highlighting: Red-highlighted sentences and underlined phrases show exactly which parts triggered AI detection signals.

Last updated: March 2026

What Is the AI Content Detector?

The AI Content Detector is a free tool that analyzes text for patterns commonly found in AI-generated writing. It uses 7 independent statistical signals to produce a composite score from 0 (likely human) to 100 (likely AI). Unlike black-box AI detectors that rely on proprietary machine learning models, every signal here is transparent and explainable.

Whether you are an educator checking student submissions, a publisher reviewing freelance content, or a writer verifying that your own work does not read like AI, this tool gives you instant, private results without any signup or data collection. All processing happens in your browser.

How the AI Detector Works

The detector evaluates your text across seven dimensions, each targeting a measurable difference between human and AI writing patterns. Each signal produces a score from 0 to 100, and the weighted average becomes the overall detection score.

  1. Paste your text into the input area. You need at least 50 words, but 200 or more words produce the most reliable results.
  2. Results appear automatically as you type. The overall score, signal breakdown, and sentence-level highlighting update in real time.
  3. Review the signal breakdown to understand which specific patterns were detected. A high score on one signal alone may not be conclusive, but multiple elevated signals together form a stronger indication.
  4. Check the text highlighting to see which sentences and phrases triggered detection. Red-highlighted sentences and underlined phrases show exactly where AI patterns were found.

Understanding the 7 Signals

Burstiness (25% weight): Measures the standard deviation of sentence lengths. Human writers naturally vary between short and long sentences, while AI produces more uniform lengths. This is the single strongest detection signal.

Vocabulary Diversity (15%): Uses Type-Token Ratio (TTR) across sliding 100-word windows to measure how varied the word choices are. AI tends to repeat the same words and phrases more than human writers.

Sentence Starters (15%): Analyzes the first word of each sentence for repetition. AI frequently starts sentences with "The", "This", "It", and "However", while human writers use more varied openings.

Transition Density (15%): Counts formal transition words like "moreover", "furthermore", and "consequently" per 100 words. AI overuses these to appear logical and well-structured.

Paragraph Uniformity (10%): Measures variation in paragraph lengths. AI generates paragraphs of similar size, while human writers produce paragraphs that vary naturally in length.

Modifier Density (10%): Tracks the frequency of adjectives and adverbs. AI writing tends to include more modifiers, especially superlatives and intensifiers.

AI Phrase Density (10%): Scans for 100+ phrases strongly associated with AI output, such as "it's important to note", "in today's digital age", and "navigate the complexities".

Frequently Asked Questions

How accurate is this AI content detector?

This detector analyzes 7 statistical signals that differ between human and AI writing, including sentence length variation (burstiness), vocabulary diversity, sentence starter patterns, transition word density, paragraph uniformity, modifier density, and AI-typical phrase frequency. It provides a reliable directional signal, but no AI detector is 100% accurate. Use results as one data point alongside your own judgment, not as definitive proof.

What is burstiness and why does it matter?

Burstiness measures the variation in sentence length throughout a text. Human writers naturally alternate between short punchy sentences and longer complex ones, producing high burstiness (high standard deviation). AI models tend to generate sentences of similar length, resulting in low burstiness. This is one of the strongest signals for detecting AI-generated content and carries the highest weight (25%) in the overall score.

Can I make AI text undetectable by editing it?

Editing AI-generated text does change its statistical patterns and can reduce detection scores. Adding sentence length variation, replacing AI-typical phrases, diversifying vocabulary, and varying paragraph lengths all make AI text harder to detect. A 'mixed' result often indicates AI text that has been edited by a human. However, heavy editing essentially transforms the text into a human-AI collaboration.

Is my text kept private?

Yes, completely. All analysis runs in your browser using JavaScript. Your text is never sent to any server, stored in any database, or accessible to anyone else. No data leaves your device. This makes the tool safe for confidential documents, academic submissions, client work, and any sensitive content.

What is the minimum text length for reliable results?

The tool requires at least 50 words to produce results, but 200 or more words are recommended for reliable analysis. Short texts do not provide enough data for the statistical signals to produce meaningful patterns. For best results, paste at least 3-4 paragraphs. You can also test different sections of a longer document separately to see if detection scores vary.

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