Limited Device-Level Visibility
Aggregate network metrics make it difficult to distinguish individual device and application behaviour.
IoT Network Intelligence
See Every Device. Understand Every Connection.
We combine DPI, GTP analytics, NWDAF and machine-learning intelligence to classify, monitor, secure and optimise traffic across large-scale connected-device ecosystems.
Industry Challenges
Millions of Connected Devices Create Millions of Variables
Connected vehicles, smart meters, industrial sensors and other IoT endpoints generate different traffic patterns, security risks and service requirements. Aggregate network statistics provide limited insight into individual device behaviour, making it harder to identify anomalies, assure service performance and manage growing IoT environments.
Undetected Device Threats
Compromised devices can continue operating while generating abnormal traffic or communicating with unauthorised destinations.
Different IoT Service Requirements
Connected vehicles, smart grids, industrial systems and other IoT services require different levels of latency, reliability and throughput.
Growing Mobility & 5G Complexity
Mobile assets introduce complex mobility and location patterns, while 5G IoT services require more granular performance and service intelligence.
Solution Overview
Bring Device-Level Intelligence to IoT Networks
We combine application-level traffic intelligence, device-behaviour profiling, signalling intelligence, location data and 5G analytics to create deeper visibility across connected ecosystems. This enables us to understand how devices behave, identify abnormal activity and manage service performance with greater precision.
01
Understand Every Device More Clearly
We combine traffic, signalling and behavioural intelligence to build a more granular view of how individual devices and applications operate across the network.
02
Detect Changes Before They Escalate
We establish behavioural baselines and continuously analyse device activity to identify anomalies, security threats and service degradation as conditions change.
03
Manage IoT Performance at Scale
We connect device, network, location and 5G intelligence to support service assurance, mobility management and optimisation across large and evolving IoT environments.
Solution Capabilities
Turn Connected-Device Traffic into Actionable Intelligence
We bring together traffic, behaviour, mobility, location and network analytics to help operations teams understand individual devices, detect abnormal activity and manage service performance across large IoT populations.
IoT Traffic & Device Intelligence
We use DPI to classify IoT traffic by device type, application and behaviour. Machine-learning models establish behavioural baselines and identify deviations in data volumes, protocols and communication patterns.
Anomaly Detection & Automated Response
We identify patterns associated with compromised devices, DDoS participation and suspicious data transfers in real time. Policy-based responses can quarantine, throttle or flag affected devices within defined operational controls.
GTP & Mobility Intelligence
We use GTP analytics to provide signalling-level visibility into device attachment, bearer management, mobility events and inter-PLMN handovers, giving operations teams deeper insight into device behaviour across the network.
5G IoT & SLA Intelligence
We combine per-device performance monitoring with NWDAF analytics to track latency, reliability, throughput, slice performance, device density and QoS compliance across 5G IoT environments.
Location & Fleet Intelligence
We add geospatial intelligence across connected fleets, assets and devices to support location-aware operations including geo-fencing, route optimisation and location-triggered policy actions.
Business Impact
Manage Connected Ecosystems with Greater Precision
Per-Device Visibility at Scale
We combine DPI and behavioural profiling to move beyond aggregate statistics and provide granular intelligence across individual devices, applications and traffic patterns.
Faster Detection of Compromised Devices
We identify abnormal or potentially malicious behaviour in real time, enabling earlier intervention before affected devices create wider network or service impact.
Differentiated IoT SLA Services
We combine per-device SLA monitoring and NWDAF analytics to support differentiated service tiers based on latency, reliability, throughput and other service requirements.
Fleet & Asset Location Intelligence
We add location intelligence to connectivity, enabling geo-fencing, fleet tracking and location-aware service delivery across mobile IoT environments.
5G IoT Readiness
We use NWDAF-based analytics to provide visibility into device density, slice performance and QoS across 5G IoT deployments.
Automated Threat Containment
We combine machine-learning detection with policy-driven response to contain abnormal device behaviour at a scale where manual intervention is impractical.
Use Cases
Intelligence Across Real-World IoT Environments
Connected Vehicle Fleet Intelligence
A connected-vehicle platform needed greater visibility across 500K+ vehicles. DPI classified navigation, OTA update, telemetry and infotainment traffic,…
A connected-vehicle platform needed greater visibility across 500K+ vehicles. DPI classified navigation, OTA update, telemetry and infotainment traffic, while location intelligence provided fleet-level visibility. Anomaly detection identified 12 vehicles with compromised telematics units within the first week.
Smart Meter Security & Compliance
A utility needed to monitor 3M smart meters for abnormal communications and unauthorised access. Device intelligence identified a…
A utility needed to monitor 3M smart meters for abnormal communications and unauthorised access. Device intelligence identified a supply-chain compromise affecting 2,000 meters, enabling the affected devices to be quarantined before sensitive data was transferred.
Enterprise IoT SLA Assurance
An IoT platform serving logistics companies needed to assure service levels across GPS trackers and environmental sensors. Device-level…
An IoT platform serving logistics companies needed to assure service levels across GPS trackers and environmental sensors. Device-level monitoring tracked latency, reliability and uptime, with automated alerts when sensor reliability fell below the committed 99.9% threshold.
5G Massive IoT Slice Analytics
An operator launching a 5G mMTC slice for smart-city sensors needed to validate performance as device volumes increased.…
An operator launching a 5G mMTC slice for smart-city sensors needed to validate performance as device volumes increased. NWDAF analytics monitored device density, throughput and reliability, identifying two cell sites requiring capacity upgrades while validating SLA performance.