Accelerated processing for mobile traffic
Operator‑grade • Scalable • Sovereign
EdgeNqoba provides a high‑throughput behavioural inference system for encrypted mobile traffic, designed for predictable performance and seamless integration with modern operator environments.
Aligned with carrier-grade acceleration frameworks, including NVIDIA BlueField‑3 DPUs and the DOCA software stack for high-performance packet processing and inline network intelligence.
Leverages hardware-accelerated GTP‑U processing and GPU‑driven inference pipelines, consistent with emerging AI‑native network architectures and AI‑RAN ecosystem evolution.
Designed to run on local edge infrastructure, ensuring data sovereignty while scaling effortlessly to meet the demands of 5G and beyond.
All heavy processing operations run on specialised accelerators, avoiding CPU bottlenecks and ensuring consistent latency.
Non-inline interception of GTP-U outer headers before decapsulation, ensuring zero payload access and preserving critical TEID mobility data.
Stateful tracking of subscriber sessions across distributed edge nodes, maintaining continuity through complex network handovers.
Extraction of over 30 proprietary behavioural metadata signatures directly on hardware-accelerated data-plane accelerators.
Real-time classification and QoE estimation powered by our protected behavioural physics engine, delivering sub-10ms latency.
EdgeNqoba performs feature engineering directly on data‑plane accelerators. This hardware‑native approach is central to our intellectual property and enables carrier‑grade performance.
Microsecond-level precision for inter-packet delay and jitter analysis.
Traffic burst detection and volume profiling for application identification.
Entropy estimation to distinguish encrypted application behaviours.
Advanced vector representations for machine learning classification.
Identify applications and user behaviours purely from metadata, ensuring zero-payload processing.
This separation guarantees real‑time data‑plane performance while maintaining flexible operator integration.
Fully accelerated to handle line-rate traffic processing.
Runs on standard infrastructure for management and orchestration.
EdgeNqoba delivers several carrier‑grade outputs directly to your existing OSS/BSS and network management systems.
EdgeNqoba's core zero-payload engine adapts to distinct operational environments. Below are the high-level data flows for our primary commercial verticals, demonstrating integration inference mechanics.
Detecting fraudulent transitions and premium-rate abuse purely through behavioural metadata anomalies, without inspecting the encrypted payload.
Non-inline capture of outer tunnel headers, preserving TEID transition chains and session timing.
Proprietary analysis comparing real-time flow symmetry and burst patterns against historical subscriber baselines.
Generation of deviation scores indicating potential SIM swap events or IRSF high-volume call patterns.
Real-time alerts pushed to operator fraud systems for immediate subscriber verification or block.
Providing national regulators with empirical, zero-payload data on OTT bandwidth consumption to resolve infrastructure cost debates.
Secure, anonymised ingestion of N3/S1-U traffic metadata from multiple MNO core edges.
EdgeNqoba classification engine identifies OTT application families (e.g., Streaming, VoIP, Social) purely via metadata signatures.
Aggregation of bandwidth consumption by hour, cell, and application type, stripping all subscriber-identifiable data.
Delivery of sovereign, audit-ready OTT traffic reports to national regulatory authorities.
Enabling dynamic 5G SA network slicing by providing the real-time traffic classification required to assign flows to the correct network slice.
Interception of encrypted PDU sessions before they traverse the core transport network.
Hardware-accelerated behavioural physics engine classifies flows into eMBB, URLLC, or mMTC profiles in real-time.
Generation of standardised metadata tags indicating the optimal network slice for each encrypted flow.
Telemetry fed to the 5G Core Network Slice Selection Function for dynamic, policy-driven steering.
Evaluate our high-performance architecture, review our technical specifications, and explore pilot opportunities for your network.