AI-Powered Routing and Revenue Optimisation

Machine learning-driven least cost routing with real-time quality scoring, predictive analytics, and automatic failover. Neural network routing engine continuously optimises every call for cost, quality, and revenue with sub-10ms decision times.

How It Works

A neural network trained on billions of CDRs spanning years of global traffic data identifies patterns invisible to traditional routing logic, predicting route quality before degradation occurs. Every active route is continuously scored across ASR, ACD, PDD, MOS, and CLI delivery rate in real time. Algorithms balance termination cost against revenue potential, factoring in customer SLAs, quality commitments, and margin targets.

Core Capabilities

ML-Driven LCR
Multi-factor route evaluation across cost, quality, historical performance, load, and time-of-day patterns. Sub-10ms routing decisions. Continuous model retraining on live data. Configurable targets: cost, quality, or balanced.

Predictive Analytics
30-minute quality forecasting by analysing ASR, PDD, and error code trends. Early warning detection for anomalies and outages. Traffic volume prediction for capacity planning. Seasonal and time-of-day pattern recognition.

Automatic Failover
Sub-second failover with zero call drops in most scenarios. Pre-ranked backup routes for every destination. Configurable quality thresholds. Automatic route recovery on issue resolution.

Quality Dimensions

ASR
Maximises call completion rates. 
ACD
Identifies routes delivering longer, higher-quality conversations. 
PDD
Minimised by routing through suppliers with fastest setup times. 
MOS
ML-predicted audio quality scoring, high-scoring routes prioritised for premium traffic. 
CLI Delivery
Tracked per route and supplier. Cost vs Quality — Configurable slider between pure cost and pure quality optimisation per customer or traffic type.

Advanced Features

A/B Route Testing
Split controlled traffic percentage between current routing and test configuration.
Traffic Pattern Analysis
Peak hours, seasonal trends, destination shifts, anomaly identification.
Dynamic Supplier Selection
Ranked on real-time performance, not static preferences. 
Historical Performance Analysis
Years of routing data with analytics tools.

Performance

Up to +12% ASR improvement (first 30 days), up to -40% PDD reduction, up to +18% margin increase, <10ms average decision time.

Revenue Engine

Margin-Aware Routing
Factors sell and buy rates into every decision, ensuring no call routed at a loss.
Volume-Tier Optimisation
Directs traffic to meet supplier commitment tiers and unlock better rates. 
Revenue Dashboards
Real-time visibility into revenue, costs, and margins per destination, customer, and supplier.