No. Statistical pattern recognition provides probabilistic estimation, not legal or academic certainty. Elevated scores indicate a heavy density of common machine patterns, but human review is always recommended before making disciplinary decisions.

Our image detection engine uses a Swin Vision Transformer running through ONNX Runtime. Rather than checking metadata (which can easily be stripped), it analyzes microscopic pixel-level denoising patterns, spatial coherence, and border degradation typical of modern diffusion models.

No. Submissions are processed entirely in volatile memory (RAM) strictly for the duration of inference and are discarded immediately after results are generated. We do not store or train models on user data.

For reliable statistical significance in perplexity and burstiness analysis, we recommend submitting at least 50 to 100 words. Short inputs under 20 words lack sufficient token distribution to reliably distinguish human writing from AI phrasing.

Yes. By evaluating token probability distributions and generation signatures across our backends, LikelyAI can identify patterns characteristic of leading AI families such as ChatGPT (OpenAI), Gemini (Google), and other generic or open-weight AI architectures.

The AI family signature is only shown when the Estimated AI Likelihood score reaches 40% or higher. Scores below 40% reflect authentic human writing with natural stylistic variation, where attributing an AI model would be inaccurate. Once machine patterns cross the 40% threshold, LikelyAI matches token distributions against known signatures from families like ChatGPT, Gemini, and generic AI architectures.

The LikelyAI Badge allows website owners to embed a dynamic SVG badge displaying real-time content authenticity scores. By attaching an optional alert email parameter to your embed snippet, our system automatically dispatches a detailed security report to your inbox whenever an evaluated page reaches or exceeds 75% AI likelihood.