ML-powered detection using TF-IDF & Logistic Regression — runs entirely in your browser. No data sent anywhere.
Paste any text and get instant AI vs. Human classification with confidence scores.
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Paste AI-generated text and get a naturally rewritten, human-sounding version — bypass AI detectors with one click.
Our pipeline converts raw text into TF-IDF feature vectors and classifies them using a trained Logistic Regression model.
Raw text is received, cleaned, and validated with a minimum 50-word requirement.
Text is transformed into 5,000-dimensional feature vectors using unigram & bigram analysis.
A Logistic Regression classifier outputs the probability of AI-generated or human-written text.
Supervised ML model using TF-IDF feature extraction and Logistic Regression classification.
Trained on 1,000+ labeled samples with 80/20 split using precision, recall, and F1-score.
Every prediction includes a confidence score so you can assess reliability before deciding.
All analysis runs in your browser. No data ever leaves your device.
Industry-standard Python ML libraries for reliable text classification.
Send a POST request to /predict and receive instant results.
Screen student essays and research papers for AI-generated content.
Screen submissions for AI-generated writing in editorial workflows.
Additional analysis for application responses and written assessments.