How we actually
detect AI text
No black box magic. Here's what we learned from months of research.
I spent weeks reading academic papers on AI detection. What I found surprised me - most commercial detectors use just one or two signals. Run the same text twice, get different scores. That's not science, that's guessing.
The truth is, there's no single "AI fingerprint." You need to look at multiple things at once. That's what we do.
We combine several signals into one score. I won't give away all the details (competitors would love that), but here's the general idea:
Sentence rhythm
Humans write with natural variation. Short sentence. Then a longer one with more detail. AI tends to be more uniform - similar lengths, similar structure. We measure how much the writing "breathes."
Word choices
AI has favorite words. "Leverage," "utilize," "crucial," "comprehensive" - these pop up way more often than in human writing. We track vocabulary patterns that give AI away.
Predictability
AI works by predicting the next word. This makes AI text weirdly... expected. Humans surprise you more. We have ways to measure this "surprise factor."
Hidden repetition
AI loves certain phrase patterns. "In order to," "it is important to note," "when it comes to" - the same structures over and over. You don't notice it reading, but the math catches it.
Here's where most detectors mess up: a news article full of quotes can look "AI-like." Technical docs follow strict patterns. Legal text is formal by nature.
Our system understands context. We trained on thousands of real examples - all kinds of writing styles. A quote-heavy article won't get falsely flagged just because it follows journalistic standards.
Most detectors only work well in English. We built ours differently - using models that understand language patterns across different writing systems. German, Spanish, Japanese, Arabic... they all work.
AI models keep getting better. GPT-4 writes differently than GPT-3. Claude writes differently than both. So we keep testing, keep learning, keep updating.
When AI gets smarter, we get smarter too. That's the deal.
Other tools swap words with synonyms or add invisible characters to trick detectors. That's lazy. And it doesn't really work across different detection tools.
We actually rewrite the content. Keep the meaning, change how it's expressed. Add natural variation, conversational flow, the little imperfections that make text feel human.
I won't share exactly how (proprietary and all that), but the philosophy is simple: real transformation, not cheap tricks.
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