Al-Driven Networks
Making Networks Smarter
Evolve into an Intelligent Network
Traditional approaches to network management can no longer keep pace with today’s network scale and dynamism. This is where Artificial Intelligence (Al) steps in-transforming networks from reactive systems into intelligent, self-optimizing ecosystems.
Al-driven networks leverage machine learning, predictive analytics, and automation to anticipate issues before they occur, optimize resource allocation in real time, and deliver superior user experiences. From automated fault detection to dynamic traffic routing, Al is enabling networks to be more resilient, efficient, and adaptive.
Some of the key Al-ML applications in networks are:
Intelligent Spectrum Utilization
Al based CSI feedback, beam management in RAN
Positioning Enhancement
Precise location accuracy- even in GPS-challenged environments
Energy Optimization
Intelligent sleep timing of systems to conserve energy
Fault Prediction & Prevention
Monitor network parameters Agentic management of remediation
Autonomous Operations
Agentic management of network operation & optimization
Tejas is contributing to global standards and creating Al-driven solutions across wireless and wireline scenarios.
Some of Our Advanced Solutions:
Universal Forecasting System
A zero-shot forecasting of KPIs
RCA Agent
Real-time event-based alarm correlation
AI-RAN
Al-native architectures for next-generation wireless networks
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