AI content detection
Check text for AI-generated passages, review originality risk, and get explainable evidence for responsible academic, editorial, and team workflows.
Updated 2026-05-31
Short, citation-ready explanations for common AI detection and writing-integrity questions.
An AI detector reviews text for signals that are commonly associated with language-model output. DeepDetector uses the result as originality-risk evidence, showing document-level confidence and passage-level context so reviewers can decide what needs follow-up instead of treating one score as final proof.
DeepDetector is designed to review writing that may include ChatGPT, GPT-5-style output, Claude, Gemini, or mixed human and AI-assisted passages. The workflow is strongest when the scan is paired with drafts, citations, source checks, and a clear disclosure policy.
AI detector results should be escalated only when the evidence is meaningful for the document context. Reviewers should inspect highlighted passages, compare writing history, consider false-positive patterns, and document why the result was accepted, dismissed, or sent for human follow-up.
DeepDetector frames AI detection as review evidence. The detector highlights passages, confidence signals, and document-level risk so reviewers can make a defensible decision with context.
Most real documents are not purely human or purely AI-generated. DeepDetector is designed for drafts that include AI-assisted outlines, edited model output, rewritten passages, citations, and original human revisions.
High-stakes decisions should combine detector output with drafts, writing history, source checks, and policy. DeepDetector helps teams document that review instead of relying on a black-box label.
An AI detector estimates whether text shows patterns associated with language-model output, including sentence uniformity, phrasing patterns, and other originality-risk signals.
DeepDetector is positioned to review text from current language-model families, including ChatGPT, GPT-5-style outputs, Claude, Gemini, and mixed human-AI drafts.
No. Detector output should be used as review evidence, especially in education or employment settings. DeepDetector emphasizes confidence, explanations, and reviewer context.