Unfox

Unfox is an AI content detector that estimates whether submitted writing is more likely to be AI-generated or human-written. It provides an overall result, probability-based scores, and sentence-level signals for reviewing essays, articles, reports, marketing copy, and other text.

What it does

Users can paste text or upload a document, then run an analysis without signing up according to the product page. Unfox examines linguistic and structural patterns, including predictability, sentence variation, and other statistical signals associated with AI-generated or human writing. Its results may identify AI, suspected AI, or human patterns, while sentence-level analysis shows which sections contributed to the overall assessment.

The detector is designed to identify writing patterns associated with major generative AI systems, including ChatGPT, Claude, Gemini, and DeepSeek. It supports 17 languages, including English, Simplified Chinese, Japanese, German, French, Spanish, Portuguese, Russian, Arabic, Dutch, Czech, Hindi, Indonesian, Italian, Korean, Turkish, and Vietnamese.

Notable capabilities

• Overall AI, suspected-AI, and human-oriented detection results with confidence or probability signals.
• Sentence-level analysis to locate sections that may deserve closer review.
• Multilingual detection across 17 supported languages.
• Paste-and-upload checking, with batch detection for reviewing multiple documents.
• API access for incorporating AI detection into another platform or workflow.

Who it helps

Students and educators can use Unfox to review essays, assignments, and academic writing before submission or during content review. Writers, freelancers, editors, and publishers can check drafts, client work, articles, or manuscripts for passages that may show AI-associated patterns. SEO teams, agencies, and businesses can use it as an initial screening step for marketing and other content handled at scale.

Like other text classifiers such as AI Detector, Unfox is intended to estimate whether writing resembles AI-generated content; it does not establish authorship or prove that a particular model produced the text.

How it fits a workflow

A typical review involves submitting text, checking the overall result, and then examining sentence-level signals to decide which passages need contextual review. Batch detection can support larger volumes, while the API is positioned for teams that want to add detection to an existing workflow. The product page states that submitted content is discarded after analysis, supporting its privacy-first positioning.

Strengths and limits

Unfox combines broad language coverage with sentence-level context rather than presenting only one percentage. Its results are probability-based signals, not verdicts. False positives and false negatives are possible, particularly with highly structured, formulaic, heavily edited, paraphrased, or mixed human-and-AI writing. The product also states that detection should be considered alongside drafts, source material, writing history, and human judgment rather than used alone for consequential decisions such as determining academic misconduct.