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AI Text Analyzer

Detect AI-generated writing patterns with 7-dimensional analysis. 100% private — all processing happens in your browser.

How AI Text Detection Works

AI text detectors analyze statistical patterns in writing to distinguish human-authored content from machine-generated text. Large language models tend to produce text with predictable vocabulary, uniform sentence lengths, and heavy use of transitional phrases. Human writing, by contrast, shows more burstiness (variability), diverse vocabulary, and natural imperfections.

The 7 Dimensions We Measure

  • Perplexity— How predictable the word choices are. AI tends to use common, safe words.
  • Burstiness— Variation in sentence length. Humans naturally mix short and long sentences.
  • Vocabulary Diversity— Ratio of unique words to total words (Type-Token Ratio).
  • Sentence Patterns— Repetition of sentence starters and uniform sentence structures.
  • Transitional Words— Overuse of formal transitions like “moreover” and “furthermore.”
  • Readability— Whether the Flesch-Kincaid score is suspiciously polished.
  • Repetition— Repeated word pairs (bigrams) indicating formulaic phrasing.

Common Mistakes

  • ✗Treating the score as a definitive verdict — no detector is 100% accurate
  • ✗Only checking short passages (under 50 words) — results are unreliable
  • ✗Ignoring context — academic writing naturally uses more transitions
  • ✗Assuming a high score means the text is definitely human-written

Pro Tips

  • ✓Analyze at least 100+ words for reliable results
  • ✓Compare multiple sections of a document, not just one paragraph
  • ✓Use this as one signal alongside your own judgment
  • ✓Edit flagged sections by varying sentence length and vocabulary

Real-World Examples

Education

Educators check student submissions for AI-generated content before grading

Content marketing

Editors verify that freelance writers deliver original, human-written articles

Publishing

Publishers screen manuscripts for undisclosed AI assistance

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About AI Text Detection

What Is AI Text Detection?

AI text detection is the process of analyzing written content to determine whether it was authored by a human or generated by an artificial intelligence system such as ChatGPT, Claude, or Gemini. Detection tools examine statistical patterns in the text — things like word frequency distributions, sentence length variability, vocabulary richness, and the density of transitional phrases.

Unlike plagiarism detection, which compares text against a database of existing documents, AI detection looks at the intrinsic statistical properties of the writing itself. Large language models produce text that is, by design, statistically average and fluent, which creates detectable patterns.

How Reliable Are AI Detectors?

No AI text detector is perfectly accurate. Studies have found that even the best detectors achieve roughly 80-90% accuracy on unmodified AI-generated text. Accuracy drops significantly when:

  • The AI text has been edited or paraphrased by a human afterward
  • The sample is very short (under 100 words)
  • The text is technical or academic (naturally uses formal patterns)
  • The AI was specifically prompted to write “naturally”

Think of AI detection as a helpful signal, not a definitive judgment. It works best when combined with other evidence and human review.

Limitations

This tool analyzes English text only. It works by examining:

  • Statistical patterns— word frequency, sentence length distribution, vocabulary diversity
  • Structural patterns— sentence starters, paragraph uniformity, transitional phrase density
  • Repetition patterns— repeated phrases, formulaic constructions

It does not use machine learning or neural networks. The analysis is entirely rule-based and runs in your browser with zero network requests. Results should be used as a screening tool, not as definitive proof.

Frequently Asked Questions

Can AI detectors detect all AI-generated text?

No. Detection accuracy varies and can produce both false positives (flagging human text as AI) and false negatives (missing AI text). Detection is most reliable on unmodified, medium-length AI outputs.

Is my text sent to a server for analysis?

No. All analysis runs entirely in your browser using JavaScript. Your text never leaves your device. There are zero network requests.

How many words do I need for accurate results?

We recommend at least 100 words. Shorter texts lack sufficient statistical signal. For best results, analyze passages of 200-500+ words.

What does “Human-like Score” mean?

A score of 0-100 where higher means the text shows more human-like patterns. A score above 60 suggests human-like writing, 30-60 is uncertain, and below 30 suggests AI-generated patterns. This is not a definitive classification.

Can I use this to detect AI in non-English text?

The analysis is optimized for English text. Non-English text may produce unreliable results, particularly the perplexity and readability dimensions.

This utility is provided for informational purposes only. KnowKit is not responsible for any errors in the output.

Frequently Asked Questions

How accurate is this AI text detector?

This tool provides a rule-based heuristic analysis, not a machine learning classifier. It is most useful as a screening tool and should be combined with human judgment. Accuracy is highest on unmodified AI outputs of 200+ words.

Does this tool send my text to a server?

No. All processing happens entirely in your browser using client-side JavaScript. Your text never leaves your device. There are zero network requests involved in the analysis.

What is burstiness in AI text detection?

Burstiness measures the variation in sentence lengths throughout a text. Human writers naturally produce a mix of short and long sentences, creating high burstiness. AI models tend to generate uniformly-sized sentences, resulting in low burstiness.

What is perplexity in AI text detection?

Perplexity measures how predictable the word choices in a text are. AI models tend to produce text with low perplexity (highly predictable word choices), while human writing shows higher perplexity due to more varied and sometimes unexpected word selections.

Can I use this tool on academic papers?

Yes, but interpret results carefully. Academic writing naturally uses formal transitions, technical vocabulary, and structured patterns that may trigger AI-like scores. The tool works best on general prose, blog posts, and informal writing.

What is the Type-Token Ratio (TTR)?

TTR is the ratio of unique words to total words. A TTR of 0.6 means 60% of words are unique. Human writing typically has higher TTR than AI-generated text, as humans naturally vary their vocabulary more.

Why do transitional phrases indicate AI writing?

Large language models are trained to produce coherent, well-structured text. They tend to overuse formal transitions like 'moreover,' 'furthermore,' 'consequently,' and 'in addition.' Human writers use these less frequently and more naturally.