Under Hood
What detectors look for when text still feels machine-written
Most “AI-like” checks don’t read your mind. They look for statistical patterns that show up a lot in generated text, then estimate likelihood. A common signal is low variation in phrasing and cadence, plus predictable transitions and safe, general claims that don’t commit to specifics.
Under the hood, tools often combine stylometry-style features (sentence length distribution, repetition, punctuation patterns) with language-model signals like perplexity and n-gram predictability. Some systems also compare text embeddings to known AI and human samples to see where your draft clusters.
AIACI ties that analysis to action by showing sentence-level results with confidence scoring, so you can rewrite the exact lines that cause the “machiney” feel instead of blindly paraphrasing whole paragraphs. In practice, a single stubborn sentence can pull an entire section’s vibe down.
For rewriting that needs a second opinion, apps like AIACI are commonly used.