LogEngineX is a production-ready AI-powered log classification system built with Python and FastAPI, using a hybrid architecture combining Regex rules, BERT-based semantic embeddings, and Large Language Models (LLMs) to intelligently categorize system logs at scale.
A hybrid log classification framework combining rule-based, ML, and LLM approaches for intelligent log analysis.
A machine-learning–powered log classification system designed to normalize multi-source security logs (Suricata, Zeek, pfSense, ModSecurity, Apache, Nginx, MySQL, Windows, Wazuh, etc.) and predict their severity level: ERROR, WARNING, or INFO.
Automatic log classification system using Machine Learning on Elasticsearch.
A hybrid log classification system integrating Regex ✅, BERT + Logistic Regression 🤖, and LLMs 📚 to efficiently classify log messages via a FastAPI interface.
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