Analyzes pasted text in seconds and returns a probability score indicating if content is human or AI-generated.
Provides a clear percentage result (e.g., 45% AI, 55% Human) rather than a simple binary flag.
Displays results with a colored progress bar (often green to red) corresponding to the human vs. AI likelihood.
Accepts long-form text inputs without a strict character or word limit advertised on the main interface.
Runs directly in a web browser without requiring software downloads, extensions, or API integrations.
SEO specialists and website owners use the detector to audit outsourced or internally produced blog posts and web copy. By verifying content is primarily human-written, they aim to maintain SEO quality standards and avoid potential search engine ranking penalties associated with low-value, AI-generated content. This helps ensure their content strategy aligns with guidelines that favor original, expert-authored material.
Educators and professors paste student submissions into the tool to screen for undisclosed use of AI chatbots like ChatGPT for essays and assignments. While not a definitive proof of cheating, a high AI probability score can flag submissions for further review and discussion about academic honesty, helping institutions uphold their integrity policies in the age of generative AI.
Content marketing agencies and freelance writers use the tool to self-check their work before delivery to clients. This provides a layer of quality assurance, demonstrating that the content is original and human-crafted, which can be a selling point. It also helps agencies vet work from subcontractors to ensure it meets contractual requirements for human authorship.
Online publishers, news editors, and journal reviewers screen submitted articles and manuscripts. The tool helps identify content that may be substantially AI-generated, which could lack nuance, fact-checking, or original insight. This allows editors to request revisions or conduct more thorough fact-checking to maintain publication standards and reader trust.
Individual users, writers, and researchers experiment with the tool to understand how detectable their own AI-assisted writing is. They might test paraphrasing techniques or compare outputs from different AI models. This use case helps users learn about the limitations of AI detectors and the evolving characteristics that distinguish human and machine text.
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