AI Text Detector
Paste text to screen AI-writing risk, false-positive risk, short-sample reliability, language profile, and human-writing signals.
How AI Text Detection Works
AI text detection screens statistical patterns in writing to estimate whether content may have been generated or heavily rewritten by AI models like ChatGPT, Claude, or Gemini. EyeSift examines perplexity, burstiness, vocabulary richness, repetition, common AI phrases, human-writing signals, and sentence-level segments. The result is a review signal, not proof.
Understanding the Results
The AI-risk score estimates AI-writing risk for the pasted sample. For medium and long samples, scores above 70% suggest AI authorship, while scores below 45% suggest human writing. For short chats, social posts, and informal Portuguese, the risk band and reliability label matter more than the percentage because there may not be enough sentence structure to classify confidently.
- Perplexity: Lower values suggest more predictable (AI-like) text
- Burstiness: Human text typically has higher burstiness with varied sentence lengths
- Vocabulary Richness: Ratio of unique words to total words
- Repetition Score: Higher values indicate more repetitive patterns
False-Positive Guardrails
Short messages, jokes, slang, voice-to-text snippets, translated text, and informal Portuguese can look statistically flat because there are too few sentence boundaries. EyeSift now lowers confidence for those samples instead of forcing a strong AI verdict. A higher-risk result needs several independent signals, such as templated assistant phrasing, formal transition density, repetitive structure, and low sentence variation.
The safest workflow is to use the score as triage: review the highlighted signals, check drafts or version history when authorship matters, and avoid treating any single detector as final proof.
Tips for Best Results
- Use 50+ words for directional triage and 150+ words for stronger confidence
- Short chat messages, one-sentence text, and informal Portuguese should be treated as low reliability
- Longer samples let the detector compare sentence variation, repetition, and vocabulary patterns
- Code, lists, translated text, and technical content may produce less reliable results
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Frequently Asked Questions
How accurate is the AI text detector?
EyeSift analyzes statistical patterns like perplexity, burstiness, vocabulary richness, repetition, AI-style phrases, and human-writing indicators to estimate AI probability. Accuracy improves with longer samples. No AI detector is 100% accurate, so results should be treated as one review signal rather than definitive proof.
Can this detect text from ChatGPT, Claude, and Gemini?
Yes, the detector analyzes patterns common to all major large language models including ChatGPT (GPT-4), Claude, Gemini, Copilot, and DeepSeek. Each model produces text with characteristic statistical fingerprints such as uniform sentence length, predictable word choices, and lower burstiness compared to human writing.
What does the perplexity score mean?
Perplexity measures how predictable or surprising the text is. AI-generated text tends to have low perplexity because language models choose statistically likely word sequences. Human writing typically has higher perplexity due to creative word choices, idioms, and unexpected sentence structures. A low perplexity score alone does not confirm AI authorship — technical or formulaic writing can also score low.
Why does my human-written text show as "AI generated"?
False positives can occur with short samples, highly formal writing, academic or technical writing, non-native English writing, translated text, or heavily edited prose. EyeSift shows sample reliability plus human-writing and AI-risk signals so the score can be interpreted with context.
Does the detector work with non-English text?
The statistical model is strongest on English prose, but EyeSift recognizes multilingual and informal writing signals such as Portuguese chat phrasing, slang, lowercase message style, and first-person language. For non-English text, treat the result as triage and prefer longer samples when possible.
Is my text stored or shared when I use this tool?
No. All text analysis is performed entirely in your browser using client-side JavaScript. Your text is never sent to any server, stored in any database, or shared with third parties. You can verify this by using the tool offline after the page has loaded.