Reduce churn, grow ARPU, and serve customers smarter, turning network, usage, and billing data into the next best offer and action.
Operators have rich usage, recharge, and network data, yet churn saves, offers, and service priorities are still reactive and generic.
Flag at-risk subscribers before they leave.
Personalized offers ranked by uplift.
Grow revenue per user with the right plan.
Anticipate top-ups and nudge in time.
Link network quality to churn risk.
Route care effort to high-value, high-risk users.
Allocate budget where it converts.
Prioritize the relationships worth keeping.
A three-week sprint that prioritizes and quantifies your highest-value AI use cases before any build.
Explore the Roadmap →Predict churn, estimate value, and recommend the right offer on one subscriber segment.
See Solutions →Yes. The engine reads usage, recharge, network, and billing signals for both models, and tunes the action to each, a recharge nudge for prepaid, a retention or upgrade offer for postpaid, against the same measured-lift standard.
A churn score tells you who's at risk. The decision engine goes one step further, it chooses the specific next-best offer or action for each at-risk subscriber, then measures whether that intervention actually reduced churn against a holdout. A score you can't act on doesn't move ARPU.
Margin floors and network-cost realities are encoded as constraints the engine has to satisfy before it recommends anything. It optimizes ARPU and retention within the economics you set, not around them.
A first pilot runs on a single segment, usually high-value churn or next-best-offer, and reports lift against a holdout within the quarter, so you see a real number before scaling across the base.
Bring your biggest churn, ARPU, or next-best-offer challenge, we'll map the highest-value place to start.
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