Telecom & Media

Network anomaly detection, churn prediction, and content recommendation systems.

Churn PredictionNetwork AIRecommendations
The Challenge

Subscriber churn and network degradation both erode revenue quietly — no single event triggers alarm, the numbers just get a little worse every month until someone finally builds the retrospective report.

Our Approach

How We Solve It

Subscriber churn and network anomalies both erode revenue quietly until the numbers show up at quarter-end. We build churn prediction, network anomaly detection, and content recommendation systems that plug into your existing OSS/BSS stack and CDN.

Capabilities

What We Build

01

Churn Prediction

Flags at-risk subscribers early enough for retention offers to work.

02

Network Anomaly Detection

Surfaces degradation and outage risk before customers report it.

03

Recommendation Engines

Content and product recommendations tuned to real usage patterns.

04

Pricing Optimization

Plan and pricing models grounded in actual usage behavior.

Delivery Process

How We Deploy It

01

Discover

We study your workflows, data, and systems to find where AI creates real leverage.

02

Design

We architect the models, agents, and integrations around your existing stack.

03

Deploy

The system ships into your environment — on-premises, cloud, or hybrid.

04

Operate

We monitor, retrain, and scale the solution as your business evolves.

Live Example

See It In Action

nezam.ai — telecom-media-ai
>Predict which subscribers are at risk of churn this month and estimate network anomaly impact

Analyzing 1.2M subscriber accounts and network telemetry across 3 regions:

Churn & Network Overview
8,400
Churn Risk Flagged
42%
Retention Save Rate
2
Network Anomalies
Churn Risk by Plan
9.4%Prepaid
3.8%Postpaid
2.1%Fiber
1.2%Enterprise
Retention: 8,400 subscribers flagged for churn in the next 30 days — mostly prepaid users hitting data caps. Targeted offer drafted, projected to save $1.1M in annual revenue.
FAQ

Common Questions

How long does implementation take?

Churn prediction models are typically live in 4-6 weeks against your existing subscriber data.

Does this integrate with our OSS/BSS stack?

Yes, we build against your existing OSS/BSS and CDN infrastructure.

How is subscriber data protected?

Data stays inside your environment where required, with the same privacy standards as your existing systems.

Want this built for your Telecom operation?

Tell us about your workflows and we'll scope a tailored AI solution.

Other Industries We Serve