No AI detector is perfect. Here's an honest look at what Airno can and can't do, how our confidence scores work, and where we fall short.
On 200+ word samples of unedited AI text (ChatGPT, Claude, Gemini). Accuracy drops on heavily edited or mixed content.
On uncompressed AI-generated images (DALL-E, Midjourney, Stable Diffusion). JPEG compression and social media re-encoding reduce accuracy.
These ranges are based on internal benchmarks and may vary by content type, length, and AI model used.
Strong signals from multiple detectors. High agreement across statistical, neural, and pattern analysis.
Moderate AI signals detected. Some detectors flag AI patterns but not all agree strongly.
Ambiguous result. Could be heavily edited AI text, AI-assisted writing, or unusual human writing.
Few AI signals found. Most detectors see human-like patterns, though some minor flags may exist.
Strong human writing signals — natural burstiness, varied vocabulary, and organic sentence structure.
Airno's ensemble of 7 detection models looks for these specific signals. No single signal is conclusive — we combine them to produce a confidence score.
Airno is a signal, not a verdict. Our scores indicate probability, not certainty. We recommend using Airno as one data point alongside human judgment — never as the sole basis for consequential decisions like academic integrity rulings.