No signup required

·Free to use

Drop a .txt file here or browse

PLAIN TEXT FILES SUPPORTED

How it works

Submit content, run forensic analysis, get an evidence-backed verdict in under five seconds

Step 1

Submit

Paste up to 50,000 characters of text or upload any image. No account or signup required.

Step 2

Analyze

7 detectors run in parallel: statistical fingerprinting, RoBERTa/DeBERTa neural classifiers, 190+ linguistic pattern rules, plus CNN artifact analysis and frequency domain inspection for images.

Step 3

Results

A confidence score with full per-detector breakdown. Suspicious spans are highlighted directly in your text so you can see exactly what triggered detection.

Real examples, real scores

See how the same 7-model ensemble produces different confidence levels across content types

0PERCENT

Likely AI-Generated

Product description text

“Experience the revolutionary power of our cutting-edge solution designed to seamlessly integrate into your workflow, leveraging state-of-the-art technology to deliver unprecedented results...”

89% AI

0PERCENT

Likely Human-Written

Customer review

“Honestly I was skeptical at first but this thing is legit. My kid spilled juice on it day one and it still works fine lol. Shipping took forever though, almost cancelled...”

12% AI

0PERCENT

Mixed / Uncertain

News article excerpt

“The committee voted 7-4 to approve the measure, which would allocate funding for infrastructure improvements across the region. Critics argue the timeline is unrealistic given current constraints...”

52% AI

What Airno analyzes

Every piece of text is examined across four dimensions that AI cannot easily fake

Writing patterns

Repetitive phrasing, hedging language, and formulaic structures common in AI text

Sentence structure

Uniformity in length and cadence that differs from natural human variation

Vocabulary diversity

Entropy and burstiness metrics that reveal how varied word choices are

Statistical signatures

Perplexity scores and token probability distributions unique to LLM outputs

How accurate is Airno?

We publish our numbers, good and bad

~85-92%

Text Detection

On 200+ word unedited AI text

~78-85%

Image Detection

On uncompressed AI-generated images

7 models

Statistical, neural, and pattern analysis running in parallel

190+ patterns

Known AI phrases, hedging, structure, and vocabulary signals

Honest limits

~8-15% false positive rate. Edited AI text is harder to catch

See full accuracy breakdown

Built for teams that care about authenticity

From classrooms to newsrooms, Airno fits your workflow

🎓

Educators

Verify student submissions and maintain academic integrity with confidence.

📰

Publishers

Screen contributed articles and ensure editorial content is human-written.

👥

HR Teams

Evaluate candidate cover letters and written assessments for authenticity.

🔬

Researchers

Audit datasets and literature reviews to flag AI-generated content.

Frequently asked questions

Common questions about how Airno's detection works and what to expect

Airno achieves approximately 85-92% accuracy on unedited AI-generated text of 200+ words, and 78-85% on AI-generated images. Accuracy improves with longer text. Short snippets (under 50 words) are significantly less reliable. We are transparent about these numbers because no detector is perfect.

Airno detects text from ChatGPT (GPT-3.5, GPT-4, GPT-4o), Claude, Gemini, LLaMA, Mistral, and most other large language models. For images, it detects output from DALL-E, Midjourney, Stable Diffusion, and similar generators. Detection works best on unedited, unparaphrased content.

Partially. If someone uses AI to draft text and then heavily edits it, detection becomes harder. Airno can often flag mixed content (where portions are AI-generated and portions are human-written) but the confidence score will typically be lower (40-65%) for blended text. The suspicious span highlighting helps identify which parts triggered detection.

No. All text and images are processed in memory only and discarded immediately after analysis. We do not store, log, or share your content. The only data we retain are anonymous aggregate statistics (total analyses run). See our Privacy Policy for full details.

Airno uses an ensemble of 7 detection models running in parallel: statistical analysis (perplexity, burstiness, vocabulary richness), a fine-tuned RoBERTa neural classifier, and pattern matching against 190+ known AI writing signatures. Each model votes independently, and scores are weighted to produce a final confidence percentage. This ensemble approach is more robust than any single detector.

We recommend at least 50 words for any meaningful analysis, and 100-200+ words for reliable results. Very short text (under 30 words) doesn't provide enough statistical signal for accurate detection. The reliability score in results reflects how confident we are given the text length.

Yes. Airno offers a free REST API, no API key required during beta. You can send POST requests to /api/v1/detect/text or /api/v1/detect/image. Rate limits are 10 text detections per minute per IP. Check our API documentation for curl, Python, and JavaScript examples.

No, and you should be skeptical of any detector that claims to be. Airno has an approximate 8-15% false positive rate (flagging human text as AI) and a similar false negative rate (missing AI text). Results should be treated as one signal among many, not as definitive proof. We show confidence intervals to help you gauge reliability.

Detection accuracy drops significantly on paraphrased content. If AI-generated text is run through a paraphrasing tool or substantially rewritten by a human, confidence scores will be lower and less reliable. Airno works best on direct, unedited AI output.

Yes, Airno is completely free during beta, both the web interface and the API. We may introduce paid tiers in the future for higher rate limits and additional features, but a free tier will always be available.

On standard benchmark test sets, Airno achieves 98%+ accuracy on clearly AI-generated, unedited text from major models. In real-world conditions (where text may be partially edited, paraphrased, or very short) accuracy ranges from 85-92% on 200+ word samples. We publish these numbers openly. No detector is infallible, and results should be treated as a calibrated signal rather than definitive proof.

Airno detects output from GPT-4, GPT-4o, GPT-3.5, Claude (Anthropic), Gemini (Google), Llama 2 and 3 (Meta), Mistral, and most other mainstream large language models. For images, it detects output from DALL-E 3, Midjourney, Stable Diffusion, and Firefly. Detection works best on unedited, unparaphrased content directly from the model.

Airno uses ensemble voting across 7 independent detectors to reduce false positives. Rather than a single classifier that can misfire, each detector contributes a weighted vote. The final score includes a confidence interval so you can see how much agreement exists across detectors. A score of 72% with low inter-detector variance is more reliable than a 72% score where detectors disagree sharply. We also report a reliability indicator based on text length.

A public REST API is coming soon. During beta, the endpoints are technically accessible at /api/v1/detect/text and /api/v1/detect/image, but formal API documentation, stable versioning, and rate limit tiers are in progress. The free tier will support 10 text detections per minute per IP. Higher limits will be available for registered users. Join the waitlist to be notified when the API launches.

Yes. Airno's image pipeline runs four parallel checks: CNN-based artifact detection trained on AI-generated images, frequency domain analysis to find GAN and diffusion model fingerprints, metadata forensics to inspect EXIF and generation signatures, and consistency analysis for lighting and noise patterns. It detects output from DALL-E, Midjourney, Stable Diffusion, and similar generators. Heavily compressed or resized images reduce detection accuracy.

What people are saying

Used by editors, educators, and content teams who need reliable AI detection

“The only detector that caught the paraphrased ChatGPT essays in our submissions.”
Content Moderator

“Airno is part of our standard intake review now. No login, no friction, just results.”
Academic Researcher

“Checked 40 articles in under ten minutes. The highlighting is genuinely useful.”
Freelance Editor

Know if it's real.Know if it's AI.

How it works

Submit

Analyze

Results

Real examples, real scores

Product description text

Customer review

News article excerpt

What Airno analyzes

Writing patterns

Sentence structure

Vocabulary diversity

Statistical signatures

How accurate is Airno?

Built for teams that care about authenticity

Educators

Publishers

HR Teams

Researchers

Frequently asked questions

What people are saying

Real examples, real scores

Product description text

Customer review

News article excerpt

Frequently asked questions

Know if it's real.
Know if it's AI.