Is Your Text AI-Generated?

AI detection tools analyze the statistical fingerprints that large language models leave in the text they generate. When a model like ChatGPT, Claude, or Gemini writes a sentence, it selects each word by predicting the most probable next token based on the preceding context. This process creates measurable patterns that differ from how humans compose text.

The two most important signals are perplexity and burstiness. Perplexity measures how predictable the word choices are -- AI text tends to have uniformly low perplexity because models consistently pick high-probability tokens. Burstiness measures variation in sentence length and complexity. Human writers naturally alternate between short, punchy sentences and longer, more complex ones, while AI output tends to be more uniform.

Our detector goes beyond these two metrics. It also evaluates vocabulary diversity, phrase repetition, syntactic patterns, and the distribution of transition words. By combining multiple signals into a single confidence score, the detector provides a more reliable result than any single metric could achieve on its own.

Universities, publishers, and employers are increasingly using AI detection tools like GPTZero, Turnitin, and Originality.ai to screen submissions. If you use AI to draft or brainstorm content, running your final text through a detector before submitting it lets you know where you stand -- and gives you a chance to revise or humanize flagged sections before someone else checks.

Students can verify that their edited essays read as genuinely human before turning them in. Content writers can ensure that articles drafted with AI assistance still pass editorial AI checks. Researchers can screen grant proposals and manuscripts to avoid false positives that could damage credibility. And hiring managers can check cover letters and writing samples when authenticity matters.

Checking your own text is not about evading rules -- it is about understanding how your writing is perceived by automated systems and taking control of the final result.

No AI detector -- ours included -- is 100% accurate. The challenge is fundamental: both humans and AI produce valid English sentences, and the statistical overlap between the two means there will always be edge cases. Short texts, highly technical writing, and non-native English can sometimes produce false positives, while carefully prompted AI output may occasionally evade detection.

Our detector mitigates these limitations by combining multiple independent signals rather than relying on any single metric. Longer text samples (200+ words) produce significantly more reliable results because the statistical patterns have more room to manifest. For the best accuracy, paste the full text rather than a short excerpt.

The 0-to-5 scoring scale is designed to give you nuance rather than a misleading binary answer. A score of 2 or 3 tells you the text falls in a gray area -- possibly AI-assisted, possibly just very clean human writing -- so you can make an informed decision about whether to revise.