About EyeSift

How our detection works. EyeSift analyzes submitted content using statistical pattern-recognition techniques (perplexity, burstiness, token distribution anomalies, stylometric fingerprints) and model-specific markers associated with common generative AI tools. No detector — ours or anyone else's — is 100% accurate, and the arms race between generators and detectors means that accuracy figures fluctuate as new models emerge. We publish current accuracy benchmarks and their confidence intervals on our AI Detection Statistics page rather than claiming fixed numbers.

When to trust an EyeSift result. Detection output is a probability, not a verdict. A "likely AI-generated" result means the content shares statistical patterns with known AI-generated samples — but short texts, heavily edited AI output, translated text, or genre-specific styles (academic, technical, legal, formulaic business writing) can all yield misleading signals.Never use EyeSift results as the sole basis for high-stakes decisions such as academic discipline, employment termination, or legal proceedings. Always combine detection results with context, human review, and corroborating evidence. Our approach and limitations are detailed on the Methodology page.

Editorial oversight. Every long-form article and reference page on EyeSift is reviewed against peer-reviewed literature in NLP and AI detection research, published benchmarks from academic AI-detection teams, and primary sources from model vendors. When a significant new detection paper is published or a major new generative model launches, we revisit the affected articles and update them. Our approach is documented on the Editorial Guidelines page.

Corrections policy. Errors happen. When a reader flags an issue — an incorrect accuracy citation, a stale model reference, a false claim about a competitor, a broken link — we investigate within 48 hours, publish the correction, and update the "Last reviewed" date at the top of the affected page. Material corrections are also noted publicly on the Editorial Guidelines page.

Independence and revenue. EyeSift is independently owned. We do not accept sponsored placements disguised as editorial, we do not run affiliate comparisons where placement is paid for, we do not sell detection credits or lead data to AI-tool vendors, and we do not recommend specific paid AI-detection services. Our revenue comes from contextual display advertising (see Privacy Policy for disclosure details), which does not influence the content, ordering, or comparisons you see in our articles or directory listings.

EyeSift is not a court-admissible forensic service, a plagiarism detector (those tools compare against known source databases — ours detects generative-AI patterns instead), a substitute for human editorial judgment, or a guarantee of content authenticity. We are a research and reference resource and a public-facing detection utility. Our limitations are inherent to the state of the art in AI-generated-content detection — no tool available today, including ours, can deliver certainty.

If you need a formal authenticity determination for legal, academic-integrity, or journalistic purposes, combine EyeSift results with independent human review, source interviews (for journalism), process evidence (writing drafts, revision history), and — where appropriate — forensic experts who can speak to methodology and limitations under oath.