What does DeepDetector check?
DeepDetector reviews writing for AI-generated text signals, including document-level risk, passage-level evidence, and patterns that may appear in ChatGPT, GPT-5-style, Claude, Gemini, or mixed human-AI drafts.
Knowledge base
Clear answers for educators, publishers, teams, and writers using DeepDetector to review AI-generated text responsibly.
DeepDetector reviews writing for AI-generated text signals, including document-level risk, passage-level evidence, and patterns that may appear in ChatGPT, GPT-5-style, Claude, Gemini, or mixed human-AI drafts.
No. AI detection should be treated as review evidence, not final proof of authorship or misconduct. High-stakes decisions should also consider drafts, writing history, citations, policy, and human judgment.
DeepDetector is positioned for current language-model writing patterns, including ChatGPT, GPT-5-style output, Claude, Gemini, and mixed AI-assisted drafts. Model-specific review pages explain how to interpret those signals responsibly.
Accuracy depends on document length, language, editing history, topic, and whether the text is fully AI-generated or mixed with human revision. DeepDetector emphasizes confidence, explainability, and review workflow rather than treating a single percentage as a verdict.
A false positive happens when human writing is flagged as AI-like. This can occur with short samples, formulaic assignments, polished templates, non-native writing, or highly edited text. Reviewers should inspect passages before making decisions.
A mixed result means some passages may carry stronger AI-writing signals than others. Review highlighted sections, compare them with drafts or sources, and decide whether revision, disclosure, or a human follow-up is appropriate.
DeepDetector is built around privacy-aware review workflows. Teams should configure retention and access controls based on their policy, and sensitive review processes should avoid unnecessary long-term storage of submitted text.
Teachers should define AI-use rules before assignments, use detector results to identify passages for review, compare drafts and citations, ask for student context when needed, and document the final decision.
Yes. API workflows can route high-risk or low-confidence documents to review, keep audit records, and integrate AI detection into publishing, education, compliance, or content operations.