Location Data Remains an Underutilized Operator Asset
Operators have access to valuable network and subscriber location intelligence, but much of its commercial potential remains untapped.
Turn Location Intelligence into Digital Revenue
We combine real-time location, DPI-derived application context, and AI/ML-powered targeting to create location-aware services, smarter engagement, and new monetization opportunities across operator and enterprise ecosystems.
Challenges
Industry Challenges
Location Alone Provides Limited Context
Knowing where subscribers are is more valuable when combined with application behavior, movement patterns, and contextual intelligence.
Generic Campaigns Struggle to Drive Engagement
Location-based marketing requires accurate targeting, relevant timing, and behavioral intelligence to improve subscriber responsiveness and campaign performance.
Enterprises Need Actionable Location Intelligence
Enterprises need location intelligence they can integrate into real operational and commercial decisions, not another isolated source of network data.
Product Overview
AI-Enhanced Location Intelligence for Services and Monetization
Our LBS/LBA platform combines cell-level, GPS, and hybrid positioning with DPI-derived application context to create richer location intelligence across operator networks. It supports geo-fencing, location-aware campaigns, footfall analytics, emergency caller location, proximity-based notifications, and enterprise API services.
ML models analyze movement patterns and subscriber behavior to predict responsiveness and optimize campaign targeting, while DPI adds application context to location data providing insight into both where subscribers are and how they are engaging with digital services.
The Outcomes Are Clear
01
Richer location intelligence
02
Smarter engagement
03
New digital revenue opportunities
Capabilities
Product Capabilities
Multi-Source Location Intelligence
Combine cell-level, GPS, and hybrid positioning to support location-aware services across different network and device environments.
Geo-Fencing
Define geographic zones and trigger relevant services, notifications, or campaign actions when eligible subscribers enter, leave, or interact within designated areas.
AI-Targeted Location-Based Advertising
Deliver location-aware campaigns using subscriber location, application context, behavioral signals, and configured audience criteria.
DPI-Enriched Location Context
Combine location information with DPI-derived application intelligence to understand both subscriber location and relevant digital activity.
AI-Powered Footfall Analytics
Analyze location and movement data to measure footfall patterns and use AI to predict movement trends across physical locations.
Predictive Campaign Optimization
Apply ML models to predict subscriber responsiveness and continuously optimize targeting to maximize campaign conversion rates.
Proximity-Based Notifications
Trigger context-aware notifications based on subscriber proximity to defined locations, services, events, or points of interest.
Emergency Caller Location
Support emergency location services, including E-911 and Advanced Mobile Location (AML), to provide accurate caller-location information where applicable.
Enterprise Location APIs
Expose location intelligence and supported analytics through APIs, enabling enterprise consumers to integrate location-aware capabilities into digital services and applications.
Process
How It Works
01
Establish Location
We combine cell-level, GPS, and hybrid positioning to determine subscriber location across supported environments.
02
Enrich with Context
DPI-derived application intelligence adds relevant digital context to location and subscriber activity.
03
Analyze Movement and Behavior
AI/ML models evaluate movement patterns, location history, and behavioral signals to generate predictive intelligence.
04
Activate Location-Aware Services
Geo-fencing, proximity notifications, campaigns, emergency location, and enterprise services use the resulting intelligence according to configured requirements.
05
Optimize Engagement
ML models analyze responsiveness and campaign performance to continuously improve targeting and conversion.
Results
Key Outcomes
New Digital Revenue Streams
Monetize operator location intelligence through enterprise APIs, targeted engagement, and location-aware digital services.
More Relevant Subscriber Engagement
Use location, application context, and behavioral intelligence to make campaigns timelier and more relevant.
Higher Campaign Conversion
Apply predictive targeting and responsiveness models to improve the effectiveness of location-based campaigns.
Richer Enterprise Intelligence
Provide enterprises with footfall, movement, proximity, and location insights that support better operational and commercial decisions.
More Actionable Subscriber Intelligence
Combine location, movement, and application context to create richer intelligence for digital services and enterprise applications.
Expanded Location-Based Services
Support commercial, enterprise, subscriber, and emergency services through a common location intelligence platform.