Check if your text will be flagged as AI-generated. Get an instant AI probability score with detailed analysis. Free, no signup required.
You paste text. We analyze it for the statistical and structural patterns that indicate AI-generated content, then return a probability score and the specific passages that triggered the detection. That's the whole job.
AI detection works by measuring the difference between how AI models generate text and how humans write it. The core signals are perplexity — how surprising each word choice is given the context — and burstiness — how much the complexity level varies within a text. AI-generated text tends to be low perplexity (predictable word choices) and low burstiness (uniform complexity throughout). Human writing tends to be more unpredictable and more variable.
Our detector runs these measurements alongside structural pattern recognition trained on 2025 and 2026 outputs from GPT-4o, Claude 3.5, Gemini 1.5, DeepSeek, Copilot, and Llama. The model identifies patterns specific to each major AI system and flags text accordingly with per-paragraph breakdown showing which sections are driving the overall score.
The score is a probability estimate, not a verdict. A score of 87% means the text has the statistical profile consistent with AI generation — it doesn't prove AI authorship. Treat scores above 70% as signals for review, not evidence of misconduct. False positives occur. Some human writers produce text that happens to match AI patterns, particularly in formal or technical writing contexts.
Paste the text you want to check into the input box. Minimum 50 words for meaningful analysis. Below that, the sample size is too small for reliable scoring. 200 words or more produces the most reliable results.
Click Detect. The output shows an overall AI probability score, a sentence-by-sentence or paragraph-by-paragraph breakdown highlighting the sections with the highest AI probability, and a brief summary of the primary patterns detected.
For content review workflows, check in sections. A 2,000-word article with one AI-generated section and four human-written sections will score lower overall than the AI section scores alone. Section-by-section checking identifies exactly which parts need attention.
Use the score as a starting point, not a conclusion. A high score on a section warrants closer reading of that section for AI patterns — formulaic structure, uniform complexity, missing specificity — rather than automatic rejection. A low score doesn't guarantee human authorship, only that the text doesn't match current AI detection models' known patterns.
AI detection became practically important in 2025 when institutional policies caught up with the technology. Schools updated academic integrity policies to treat AI-generated work submitted without disclosure as academic misconduct. Publishers added AI content policies to submission guidelines. Many employers started screening writing samples for AI generation before making hiring decisions.
The problem is that detection is imperfect and the policies often treat imperfect detection as if it were proof. A student whose legitimate work happens to score 85% on an AI detector may face an academic integrity inquiry. A freelancer whose genuine writing scores high may lose a client. A job applicant whose writing sample triggers a flag may be screened out.
The response to this asymmetry is to know your score before someone else checks. If your legitimate writing scores high on AI detectors, that's information you can act on — either by revising toward lower-scoring phrasing or by understanding where the false positive pattern is and addressing it. If you used AI assistance in your workflow and want to know whether the output is detectable, checking it yourself gives you that information before submission.
The practical workflow is detector first, humanizer second. Check → score too high → humanize → check again → score acceptable → submit. This process takes minutes and removes the uncertainty of not knowing whether your document will trigger a flag.