An AI text scanner that actually works.

What Is an AI Text Scanner?

An AI text scanner is a tool that analyzes written content and calculates the probability that it was generated — fully or partially — by a large language model. As tools like ChatGPT, Claude, and Gemini become standard in academic and professional settings, the ability to identify AI-generated writing has become essential for educators, publishers, HR departments, and content teams.

Unlike plagiarism detectors, an AI text scanner examines statistical patterns specific to machine-generated prose: sentence rhythm, lexical diversity, structural predictability, and the subtle linguistic signatures that emerge from how language models complete tokens. The result is a probability score — not a verdict, but a meaningful signal that informs human review.

How to Use the AI Text Scanner

Running a scan takes under a minute. Here is exactly what to do:

1. Paste or upload your text. Enter text directly into the input area above, or upload a supported file (.txt, .doc, .docx, .pdf). Results are most reliable on passages of 100 words or more.
2. Click “Scan for AI.” Processing begins immediately. A progress bar shows each analysis stage in real time — from structural parsing through cross-model pattern matching.
3. Review your score. Within seconds you receive an AI probability percentage alongside an initial sentence-level preview. Sentences with elevated confidence scores are highlighted.
4. Access the full report. The complete breakdown — sentence-level confidence intervals, model attribution, and readability analysis — is available on the results page.

No account or sign-up is required to run a basic scan. All text is processed in memory and immediately discarded; nothing is stored on our servers.

AI Text Scanner vs. Other Detection Tools

Not all AI detectors perform equally. The critical differentiators are false positive rate, sentence-level granularity, AI model coverage, and accessibility without a paid subscription. Here is how this tool compares to the most widely used alternatives:

Tools like GPTZero offer sentence-level highlighting but have drawn criticism for flagging ESL and formal academic prose as AI-generated. Originality.ai is well-suited for bulk content teams but requires a paid subscription and lacks per-sentence granularity. Turnitin integrates deeply with LMS platforms but is unavailable to individual users outside institutional licenses.

Who Uses an AI Text Scanner

Educators and Academic Institutions

Academic integrity is the primary use case. As students gain access to generative AI capable of producing coherent essays and research papers at scale, instructors need reliable tools to assess the authenticity of submitted work. An AI text scanner provides a starting point for that review — not as a final verdict, but as a data point to weigh alongside other evidence of a student’s genuine engagement with a topic.

For this use case, a low false positive rate matters more than maximum sensitivity. Incorrectly flagging a genuine student — particularly one writing in English as a second language — carries serious academic consequences. This scanner is specifically calibrated to reduce that risk.

Content Teams and Publishers

Editorial teams at media companies, content marketing agencies, and publishing houses increasingly use AI detection as part of their quality pipeline. Freelance contributors may use AI writing tools without disclosure, and maintaining content authenticity is both a quality standard and, in some contexts, a legal consideration. A quick scan before publication adds a lightweight verification step to any editorial workflow.

For SEO-focused teams there is an additional consideration: search engines have signaled that low-quality, mass-produced AI content may be subject to ranking penalties. Detecting and reviewing flagged content before publishing is a straightforward quality control measure.

HR and Recruitment

Written assessments, cover letters, and screening exercises submitted during hiring processes are increasingly AI-assisted. Recruiters who want to evaluate a candidate’s actual communication ability — rather than their prompting ability — use AI detection as part of their screening review. A text scan takes seconds and can flag submissions that warrant a closer look before moving a candidate forward.

Understanding Your Scan Results

The scan produces an overall AI probability score expressed as a percentage. Scores above 70% suggest predominantly AI-generated content; below 30% suggests predominantly human writing. The range between 30% and 70% is a mixed zone where partial AI assistance, heavily edited AI output, or stylistically formal human prose can all produce similar scores.

The more actionable layer is the sentence-level breakdown in the full report. Each sentence receives its own confidence score, and sentences above threshold are highlighted. This shows whether flagging is consistent throughout (suggesting end-to-end generation) or clustered in specific sections (suggesting targeted AI assistance or partial rewriting).

The model attribution section identifies which AI system the writing most closely resembles — GPT, Claude, Gemini, or others. This is useful context when deciding how to act on a result. No AI detector is infallible: heavy manual editing of AI output reduces detection confidence, and paraphrasing tools applied to AI text can lower detectability further. Treat results as evidence to inform a human judgment, not as proof in isolation.