Advanced algorithms and architecture powering next-generation RAN optimization
Our proprietary ML models continuously learn from network behavior, enabling predictive optimization and autonomous decision-making.
Multi-layer architectures for complex pattern recognition in network traffic and performance metrics
Adaptive algorithms that optimize parameters through trial-and-error learning
LSTM and Transformer models for accurate traffic prediction and capacity planning
Built on modern cloud-native principles with microservices architecture for maximum flexibility and scalability.
Independently deployable services for site planning, SON, and capacity management
Kubernetes-based deployment with auto-scaling and self-healing capabilities
Real-time processing with message queues and streaming data pipelines
Genetic algorithms and particle swarm optimization for site selection with competing objectives
Advanced 3D ray-tracing and diffraction models for accurate coverage prediction
Real-time spectrum and power optimization using linear programming and heuristics
Connect with your existing telecom infrastructure
Standard HTTP/JSON interfaces for easy integration
Compatible with PostgreSQL, MongoDB, and time-series databases
Pre-built connectors for major telecom management systems
Support for CSV, JSON, and industry-standard formats
Deep dive into our algorithms, APIs, and architecture with comprehensive technical resources.
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