Arabic AI Detector
Every mainstream detector was trained on English and merely tolerates Arabic. Sahihly is the opposite: an engine that reasons about Arabic morphology, diacritics, and register natively — paste Arabic text below and see the difference.
Why English tools fail on Arabic
Arabic builds dozens of word forms from a single root, marks meaning with optional diacritics, and moves freely between verbal and nominal sentences. Detectors trained on English statistics see all of that as noise — which produces random scores and unfair false accusations for Arabic writers.
What native support actually means
Sahihly's engine evaluates the signals that matter in Arabic: root-pattern variety, the rhythm of connected prose, register consistency (فصحى vs simplified), and the stock transitions Arabic AI text overuses — علاوة على ذلك، في الختام، من الجدير بالذكر.
From detection to better writing
A score alone doesn't help you improve. Every Arabic analysis highlights the machine-flavored sentences and includes a style report — rhythm variety, vocabulary richness, AI-pattern count — so you know exactly which lines to rework, then the humanizer can rewrite them in fluent فصحى.
Fair by design
Because false accusations hit Arabic speakers hardest with English-only tools, Sahihly treats every result as an estimate, shows its reasoning, and never claims courtroom certainty. Use scores to revise your work — not to judge someone else's.
Frequently asked questions
Yes. English-trained detectors don't model Arabic morphology, so their Arabic scores are close to noise. Sahihly evaluates Arabic-specific signals and shows per-sentence reasoning you can verify yourself.