About AI Checker

The team behind every detection score on ai-checker.co.

AI Checker is a small editorial and engineering team building the free AI content detector we wanted to use ourselves. We calibrate detection signatures every time a major model ships, audit every public page for accuracy, and publish how the underlying detection pipeline works in plain language.

Mission

Help humans tell AI text from human writing — without selling them out.

Most AI detectors charge per check, lock the API behind enterprise sales, or quietly sell the text you submit to a data broker. That isn't us. We treat the free tier as the product: no signup, no daily character traps, and no model training on your submissions. The paid tier exists for teams that need volume, audit logs, and SLA — not as a tax on the free one.

We are also honest about what AI detection can and cannot do. No detector is 100% accurate. State-of-the-art tools land between 95–98% on unedited model output, and false positives on real human writing are rare but real. We publish the accuracy numbers per model, per language, and per difficulty band so you can use the score as evidence rather than a verdict.

Methodology

How we calibrate, audit, and update detection.

Every detection score on AI Checker is the combination of three independent signals: perplexity (how predictable the text is to a reference language model), burstiness (variation in sentence length and rhythm), and lexical fingerprinting (model-specific phrasing tells). When a new model ships from OpenAI, Anthropic, Google, Meta or Mistral, we collect a baseline corpus, retrain the per-model fingerprint head, and update the public accuracy numbers.

Editorial pages — every model profile, audience guide, and comparison — are written by AI Checker editors and reviewed against the live detection pipeline before publish. If a claim cannot be verified against current model behaviour, it is removed. We re-audit the full set of programmatic pages quarterly; the date the page was last reviewed is in the content metadata of every URL.

Editorial team

AI Checker Editorial Team

The AI Checker editorial team writes, reviews, and signs off every public page on this site. The team is composed of machine-learning engineers, classroom-experienced educators, and editors with newsroom backgrounds. We do not use ghost authors, do not auto-publish AI-generated drafts without human review, and credit the editorial team — not a single anonymous brand voice — on every long-form page.

Areas of focus: AI content detection, large language model fingerprinting, perplexity analysis, burstiness scoring, academic integrity workflows, and editorial standards for AI-assisted publishing. Reach the editorial team at editorial@ai-checker.co.

Editorial standards

How we decide what counts as accurate.

  • Accuracy claims are sourced. Numbers like “95% accuracy” come from a measurable internal benchmark, not a marketing slide. The benchmark suite is refreshed quarterly.
  • No fabricated reviews. We do not publish AggregateRating schema until we have real customer reviews to back it. Faking review markup is a Google policy violation and a credibility hit.
  • Corrections are visible. When a published page is wrong, we update it with a dated correction note rather than quietly editing.
  • AI scores are evidence, not verdicts. Every page where it matters carries the same disclaimer: an AI score should inform a human review, never replace one.
Contact

Reach the team.