Opensource AI Content Detection

Identify sensitive or AI-generated content in documents with precision using ZoryaTrace advanced NLP algorithms

Full document scanning with color-coded results (red for suspicious, green for neutral content)

Advanced NLP algorithms for accurate classification

Detailed reports including precision, recall, and F-score for model evaluation

Works seamlessly on Windows, Mac, Linux, and mobile devices

Adapt the model to your specific needs with custom training data

All processing happens locally - your documents never leave your device

Why Choose ZoryaTrace?

See how we compare to other solutions.

Feature	ZoryaTrace	Other Solutions
Open Source	✅ Transparent and modifiable	❌ Often proprietary and closed-source
Privacy-focused	✅ No user tracking, fully local processing	❌ Often cloud-based, collects user data
Security	✅ Local execution, no external data leaks	❌ Data sent to third-party servers
Efficiency	✅ Optimized TF-IDF & Naive Bayes, few seconds analysis	⚠️ Can be slow due to complex models or API calls
Ease of Use	✅ Easy setup	⚠️ Usually easy, but sometimes requires API keys or dependencies
Customization	✅ Fully customizable training dataset	❌ Limited or no customization options
Lightweight	✅ Minimal dependencies, runs on low-end devices	❌ Heavy dependencies, requires cloud infrastructure
No API Limits	✅ Works offline, no request limits	❌ API-based, limited free requests
Modern LLMs detection	❌ May struggle with hightly creative AI texts from modern LLMs	✅ Hightly creative AI text is often better detected
Human/AI merged content	❌ May struggle with human-edited AI content	✅ Human/AI merged content may be betters supported

Watch how ZoryaTrace analyzes documents in real-time

Available for all major platforms

System Requirements: Python 3.8+, 1GB RAM (4GB recommended), 200MB disk space