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AI testing & review · Italy

Cobalynx

Free AI detector with published error rates

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DR by Ahrefs
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Ahrefs Domain Rating benchmarked 27 Oct 2026, rebuilt 27 Oct 2026.

A free AI text detector that reports calibrated probabilities and published error rates instead of certainty, with file provenance checking.

What it is

Screenshot of the Cobalynx homepage
cobalynx.com, as visitors see it

Cobalynx is a free AI text detector designed to minimize false accusations rather than maximize them. It analyzes text for patterns that indicate AI generation and reports results as calibrated probabilities backed by published error rates, never as proof. The tool refuses to guess on borderline cases, returning "inconclusive" when evidence is insufficient. It requires a minimum of 150 words and offers no signup. Beyond text analysis, Cobalynx checks file provenance through Content Credentials (C2PA) and document metadata. All data is processed in memory and deleted immediately after delivering results, never stored or used for training.

What it is built with

  • Calibrated probability scores with published error rates
  • Inconclusive verdicts for borderline cases
  • Minimum 150 word requirement
  • Content Credentials (C2PA) file checking
  • Document metadata analysis
  • Free human-text certification with downloadable PDF badge
  • No signup or account required
  • Private processing with no data storage

Pricing

Pricing model: Free

No payment required. Free tier allows 10 certification requests per day per IP.

Cobalynx metrics

Benchmarks for cobalynx.com: Ahrefs Domain Rating and Majestic link data, with the change since the last build.
MetricValue
Domain Rating0 no change since last check
Trust Flow2 no change since last check
Citation Flow13 no change since last check
Referring domains1 no change since last check
External backlinks25 no change since last check

Ahrefs Domain Rating benchmarked 27 Oct 2026, rebuilt 27 Oct 2026. Main build topic: Regional/Asia (2). Majestic benchmarked 27 Oct 2026, rebuilt 27 Oct 2026. Link data built by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.

Cobalynx domain build sheet

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Public RDAP record, last read 27 Oct 2026, 00:50 UTC.
Domain age5 months
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Questions from the bench

How do AI detectors work?
AI detectors analyze writing patterns that humans wouldn't notice, such as word predictability and sentence rhythm, then compare these patterns against large collections of writing where authorship is known. The detector provides an estimate of likelihood rather than definitive proof, and Cobalynx publishes its error rates so users can see how often the estimate was wrong.
What is a false positive and what is Cobalynx's rate?
A false positive occurs when a person wrote text but the software incorrectly identified it as machine-written. This is the most damaging type of error. Cobalynx's false-positive rate is 2.1% (14 of 670 texts), with a statistical upper bound of 3.5%, and the thresholds are set to keep confident wrong accusations as close to zero as possible.
Can Cobalynx prove a text is human?
No. No AI detection tool can prove a text was written by a human. Cobalynx provides an AI-likelihood score tested against real outcomes, showing how often texts scoring similarly turned out to come from AI. The tool never offers human-verified certification because that technology does not exist.
Do AI detectors discriminate against non-native English speakers?
Yes. Mainstream AI detection tools flag non-native writing far more often than they should. A 2023 Stanford study found that more than 60% of essays written by non-native speakers were flagged by seven popular tools. Cobalynx measured its own error rate on ESL writing and publishes it separately alongside other error metrics.
Can AI writing be detected after paraphrasing or “humanizers”?
Less well. Text that a person rewrote on purpose so it would slip past a detector is the hardest case there is, for every tool on the market and for ours as well, so we ran that case on purpose and put the result out with the rest. Our published results include a test split where the AI text had been run through a paraphraser first, and you can see how the detector did on it (the good and the bad) on the evidence page.

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