Overview
DetectorBot is an advanced AI content detection tool that accurately identifies text generated by leading AI models like ChatGPT, Claude, and Gemini. Our proprietary algorithms analyze writing patterns and linguistic markers to determine whether content was created by artificial intelligence, even after editing or refinement. The platform provides instant, detailed results through an intuitive free interface that anyone can use.
Features
- Comprehensive Analysis: Get section-by-section breakdowns with confidence scores showing exactly which parts of your text may be AI-generated
- Real-Time Processing: Receive detailed reports within seconds for any text over 80 words
- Multi-Model Detection: Identify content from all major AI language models including ChatGPT, Claude, and Gemini
- Free Access: Unlimited scans at no cost, with no registration required
- Refined Detection: Capable of identifying AI content even after human editing and revision
- Visual Results: Clear highlighting and percentage breakdowns make results easy to understand
Use cases
- Educators verifying student assignments and detecting potential AI plagiarism
- Content creators ensuring originality in their work
- Publishers screening submissions for AI-generated content
- Students checking their writing to maintain academic integrity
- Businesses validating marketing content and communications
- Researchers verifying authenticity of written materials
Comments
Makers
Comments
Hi everyone! I built DetectorBot after experiencing firsthand the challenges of verifying content authenticity in my role as a university teaching assistant. When students started using AI tools, we needed a reliable way to maintain academic integrity while acknowledging that AI is becoming part of the writing process. What makes DetectorBot different is that we're not trying to "catch" people - instead, we want to promote transparency around AI use. I spent six months developing our detection algorithms, testing them against thousands of real-world examples, and refining them based on user feedback. Many of the features, like the section-by-section breakdown and confidence scores, came directly from conversations with educators and writers who needed more nuanced insights than a simple "AI or not" result.
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Hi everyone! I built DetectorBot after experiencing firsthand the challenges of verifying content authenticity in my role as a university teaching assistant. When students started using AI tools, we needed a reliable way to maintain academic integrity while acknowledging that AI is becoming part of the writing process. What makes DetectorBot different is that we're not trying to "catch" people - instead, we want to promote transparency around AI use. I spent six months developing our detection algorithms, testing them against thousands of real-world examples, and refining them based on user feedback. Many of the features, like the section-by-section breakdown and confidence scores, came directly from conversations with educators and writers who needed more nuanced insights than a simple "AI or not" result.