Enhance Customer Lifetime Value with AI-powered, Machine Learning
-Driven Telecom Customer Value Management Platform

Magik is built on an AI/ML core, offering telecom operators: supervised learning models for churn prediction, fraud detection, and credit risk scoring; unsupervised clustering for subscriber segmentation; deep learning for network anomaly detection; natural language processing for social sentiment analysis; and reinforcement learning for dynamic offer optimisation. These models run on live telecom data — CDRs, signalling events, billing records — delivering predictions that directly drive commercial and operational decisions.

Magik's AI churn prediction engine analyses hundreds of behavioural signals — including declining usage trends, reduced top-up frequency, increased complaint volume, competitor SIM insertion events, and network quality degradation — to generate individual subscriber churn probability scores. These scores feed automated retention workflows: high-risk subscribers receive targeted retention offers through the most effective channel, typically reducing voluntary churn by 15–30% within the first year of deployment.

Yes. Magik applies real-time AI fraud detection to live network event streams, identifying SIM box fraud, IRSF, wangiri, subscription fraud, and roaming fraud within seconds of suspicious activity beginning. Anomaly detection models establish normal behavioural baselines for every subscriber and network element, flagging deviations that match known fraud patterns. Automated case creation and blocking rules can be triggered without human intervention, minimising fraud losses.

Magik's AI personalisation engine builds real-time subscriber intelligence profiles combining usage behaviour, device type, location patterns, lifecycle stage, and propensity scores for various products. These profiles drive Next Best Offer (NBO) and Next Best Action (NBA) engines that recommend individualised bundles, upgrade prompts, and promotional offers. Recommendations are served through campaign management systems, self-care apps, USSD menus, and retail touchpoints — maximising offer relevance and conversion.

Yes. Magik integrates with Generative AI and LLM capabilities to automate insight narration and report generation. Instead of dashboards that require manual interpretation, Magik's GenAI layer generates natural language summaries of KPI movements, anomalies, and recommended actions — making analytics accessible to non-technical business stakeholders. Automated daily briefings, alert narratives, and executive summaries can be generated and distributed without analyst intervention.

Magik is 6D Technologies' AI-powered Big Data Analytics platform purpose-built for telecoms. Unlike generic BI tools that require extensive customisation to handle CDR structures and telecom business logic, Magik comes pre-loaded with telecom-specific AI models, KPI frameworks, and use case templates. Its AI engines are trained on telecom data from day one, delivering accurate fraud detection, churn prediction, and personalisation models without months of custom model development.

Magik's AI network analytics module processes real-time network performance data — including KPIs from RAN, core, and transport layers — to predict congestion, detect degradation before it impacts subscribers, and correlate network events with customer experience metrics. AI root cause analysis accelerates fault diagnosis, while predictive capacity models guide network investment decisions, ensuring engineering teams focus on the highest-impact optimisation opportunities.