Real-time AI analytics and automation for smarter decisions and cost savings
RAIN’s visual interface gives you real-time, continuous and actionable data-driven insights for smarter and proactive decision making. Say goodbye to data silos.
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Customisable dashboard view of the entire network
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“Zoom-in / zoom-out” for each site
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Real-time analytics and insights for timely action
AI-driven energy management, with optimised power supply and energy storage, and AI/ML based demand prediction
- Reduce electricity costs via peak shaving
- Maximise use of renewable energy
- Decrease energy consumption and waste
AI-based data analytics to identify inefficiencies in AC vs. DC power conversion, with real-time data monitoring of the rectifier
- Enhance energy usage with a higher efficiency rectifier
- Provide accurate real-time data on energy consumption to tenants
- Replace manual processes with automated reporting and billing
AI-powered incident diagnosis and smart alarm management for efficient service
AI/ML algorithms used to analyze all operational data and identify the root cause of an incident. Automated reporting with diagnosis on the issue generated for field service team.
- Identify problems remotely and avoid unnecessary site visits
- Enhance efficiency of service visits
- Reduce maintenance costs
Advanced alarm management using predictive analytics and ML techniques are used to leverage historical data, real-time sensor readings, and advanced algorithms to identify patterns, anomalies, and potential alarm triggers. ML algorithms can continuously adapt and optimize alarm limits.
- Eliminate false or duplicate alarms and improve the accuracy of alarm notifications
- Categorize alarms based on their priority, severity, and relevance
- Present alarms clearly and intuitively through a single visual interface
AI-driven HVAC optimization: reduce energy use, detect anomalies, and extend equipment life
AI-driven algorithms continuously analyse data from various sensors and adapt HVAC system operation to real-time conditions
- Reduce energy consumption via optimised running time
- Realise significant energy cost savingsEliminate false or duplicate alarms and improve the accuracy of alarm notifications
Anomaly detection via holistic IoT based monitoring (e.g. sound, vibration, air quality, temperature, energy consumption) and machine learning algorithms
- Replace mission-critical parts (e.g. filter) before equipment overheating or failure
- Optimise maintenance schedule and asset lifetime
-
Customisable dashboard view of the entire network
-
“Zoom-in / zoom-out” for each site
-
Real-time analytics and insights for timely action
AI-driven energy management, with optimised power supply and energy storage, and AI/ML based demand prediction
- Reduce electricity costs via peak shaving
- Maximise use of renewable energy
- Decrease energy consumption and waste
AI-based data analytics to identify inefficiencies in AC vs. DC power conversion, with real-time data monitoring of the rectifier
- Enhance energy usage with a higher efficiency rectifier
- Provide accurate real-time data on energy consumption to tenants
- Replace manual processes with automated reporting and billing
AI-powered incident diagnosis and smart alarm management for efficient service
AI/ML algorithms used to analyze all operational data and identify the root cause of an incident. Automated reporting with diagnosis on the issue generated for field service team.
- Identify problems remotely and avoid unnecessary site visits
- Enhance efficiency of service visits
- Reduce maintenance costs
Advanced alarm management using predictive analytics and ML techniques are used to leverage historical data, real-time sensor readings, and advanced algorithms to identify patterns, anomalies, and potential alarm triggers. ML algorithms can continuously adapt and optimize alarm limits.
- Eliminate false or duplicate alarms and improve the accuracy of alarm notifications
- Categorize alarms based on their priority, severity, and relevance
- Present alarms clearly and intuitively through a single visual interface
AI-driven HVAC optimization: reduce energy use, detect anomalies, and extend equipment life
AI-driven algorithms continuously analyse data from various sensors and adapt HVAC system operation to real-time conditions
- Reduce energy consumption via optimised running time
- Realise significant energy cost savingsEliminate false or duplicate alarms and improve the accuracy of alarm notifications
Anomaly detection via holistic IoT based monitoring (e.g. sound, vibration, air quality, temperature, energy consumption) and machine learning algorithms
- Replace mission-critical parts (e.g. filter) before equipment overheating or failure
- Optimise maintenance schedule and asset lifetime
How RAIN helps mobile operators and mobile tower companies
AI at the core
Redefine operational management, deliver unmatched efficiency and reliability.
Improve decision making
No more manual data collection. Make informed decisions with timely information.
Save costs
Reduce operational costs by identifying and addressing energy inefficiencies.
Scalable solution
A scalable, customizable solution allowing you to start small and grow with your tower network.
Seamless integrations
Enhance operational efficiency across your entire telecom infrastructure.
Want a tour of RAIN?
Book a demo with an expert today.
Ready to see RAIN in action?
Chat face-to-face with a RAIN specialist and see why telco tower companies trust us to embed AI throughout tower operations processes, including predictive maintenance, automated fault detection and real-time optimization.