A modular, service-oriented system combining Next.js frontend, FastAPI backend, and Neo4j graph analytics for comprehensive campus entity resolution and security monitoring.
Comprehensive entity resolution and security monitoring powered by advanced AI and graph analytics
Multi-modal fusion with confidence scoring for accurate entity identification and linking across campus systems.
Neo4j-powered relationship mapping for entity linking, gap detection, and pattern recognition.
LSTM and XGBoost models for location prediction and anomaly detection with explainable results.
Real-time anomaly detection and predictive monitoring using ML models trained on campus activity data.
Graph-based timeline visualization for tracking entity movements and interactions over time.
Secure authentication and authorization with Prisma ORM for user data management.
Next.js Frontend on Vercel
Interactive dashboard for entity queries, timeline visualization, and anomaly monitoring with SSR and edge caching.
FastAPI Backend
Neo4j Graph Database
ML Prediction Models
TensorFlow LSTM and XGBoost for location prediction with explainable AI.
Interested in implementing Fazri Analyzer for your campus? Contact us for a demo.