NITRO Location Intelligence
The industry standard for RAN intelligence: now with AI, turning every subscriber interaction into automated, measurable action across your network.
VIAVI NITRO Location Intelligence continuously captures, locates, and analyzes every subscriber and device interaction on your mobile network down to building-level accuracy. Trusted by 50+ operators including 10+ Tier-1 CSPs on four continents, it provides the most comprehensive geolocated data feed available, enabling operators to optimize performance, protect customer experience, reduce costs, and unlock new revenue streams. With the recently available AI Assistant, that intelligence is now accessible to every team through natural language, no specialist skills required.
The Network Data Gap
Mobile operators are sitting on one of the most valuable datasets in the world with billions of daily subscriber interactions, location records, and radio performance signals. Yet most of this data remains trapped in siloed systems, analyzed manually by specialist engineers, and acted on too slowly to prevent degraded customer experience.
The result: optimization decisions are made on aggregate KPIs that mask where real users are suffering. Drive testing consumes engineering capacity that could be spent on higher-value work. Rogue devices silently degrade network quality while root cause stays invisible. And the shift to cloud-native, disaggregated RAN architectures is adding complexity faster than traditional tools can absorb it.
Operators need an intelligence layer that transforms raw network data into automated, subscriber-aware action and not more dashboards to manage manually.
Proven at Global Scale
VIAVI has spent over 20 years building the foundational technology for mobile network geolocation holding key patents and earning recognition as the industry standard across every major generation from 2G to 5G.
Today, NITRO Location Intelligence geolocates nearly one billion mobile subscribers and devices every single day. Built on the VIAVI NITRO cloud-native platform, it delivers a fast, near real-time geolocated data feed that is precise enough for operational visibility, rich enough for AI model training, and open enough to feed any downstream analytics or automation system.
What NITRO Location Intelligence Does
A complete portfolio of RAN intelligence capabilities each solving a specific operational or business challenge, all powered by the same geolocated subscriber data foundation.
Use Cases
AI Assistant
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NITRO LI's AI Assistant puts the full power of the platform's geolocated data into a natural language interface accessible to any user, not just specialist RF engineers. Query subscriber experience, generate CQX cluster reports, analyze L3 signaling, detect fraud patterns, and receive prioritized recommendations all through a conversational interface connected directly to live NITRO LI data.
Flexible deployment: cloud, virtual private cloud, or fully on premises for operators with data sovereignty requirements. No customer data is sent as part of telemetry collection.
Outcome: Expert-level RAN analysis in minutes, not hours. Scales RF expertise across NOC, planning, and customer care teams without adding headcount.
End-to-End RAN Optimization
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Automate the full optimization lifecycle from identifying problem areas using real subscriber data, to finding the best antenna configuration via a Digital Twin engine, to generating automated before/after assessment reports. No drive testing required.
Outcome: 80% reduction in drive testing. 5–10x faster cell cluster optimization.
Customer Experience Monitoring
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Move beyond aggregate KPIs. NITRO LI correlates per-subscriber radio conditions with core network data to build a true picture of Quality of Experience identifying chronic subscribers in persistent poor-quality areas, not just cells with degraded averages.
Outcome: Identify high-impact problem areas earlier. Prioritize investments based on actual user experience, not network averages.
Device Performance Analysis
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A small number of faulty or firmware-affected devices can silently degrade KPIs across entire cell clusters misdirecting both OPEX and CAPEX. NITRO LI's geolocated device intelligence detects rogue devices, validates their impact at TAC and model level, and maps degradation hotspots precisely.
RAN Energy Savings
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Reduce energy consumption without compromising subscriber QoE. NITRO LI uses subscriber-centric data and Digital Twin predictive analytics to identify cells and carriers that can be switched off with full visibility into QoE impact before any change is made.
Site Decommissioning
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Safely identify and decommission redundant sites using virtual simulation without powering anything off. NITRO LI models how traffic redistributes to neighboring cells, giving operators the confidence to act on infrastructure decisions that were previously too risky.
Outcome: $500K CapEx savings + $150K+ annual OpEx reduction per decommissioned site.
Data Monetization
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NITRO LI generates the most comprehensive geolocated subscriber mobility data feed available. Through NITRO DataOps, operators can package and deliver this data for internal analytics platforms, AI model training, or external monetization use cases including targeted marketing, transportation intelligence, and emergency services.
Outcome: New revenue streams from existing network data. Privacy-aware feeds built for downstream AI workloads.
Open RAN Integration
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Cloud-native xApp and rApp for the Distributed RIC delivering precise geolocation data to the O-RAN ecosystem and enabling intent-based RAN optimization automation natively within the Open RAN architecture.
Outcome: Subscriber-centric intelligence inside your RIC. Automation without architectural compromise.
Your Network Data as a Strategic Asset
While large language models are trained on internet-scale text, and generative AI models on visual data, telecom operators are uniquely positioned to train sovereign AI models on something far more valuable real-world subscriber mobility data.
VIAVI provides the curated, high-quality, privacy-aware data feeds that make this possible. Operators working on next-generation AI use cases from network automation to location-aware services can leverage NITRO LI's geolocated dataset as the foundation for models that no one outside their network can replicate.
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