In the telecoms industry, customer expectations are evolving faster than ever — The traditional break-fix model is no longer sufficient. Instead, telecom operators need to turn to AI-powered proactive care to deliver support before problems are even noticed by customers. The goal? Maximizing Net Promoter Scores (NPS), reducing churn, and turning customer support into a competitive advantage.
The High Cost of Reactive Support
Customer loyalty is fragile. A single technical issue can disrupt the experience and cause dissatisfaction and when a customer calls to report a problem, the damage is already done. Every unresolved issue translates to frustration, increased support costs, and potential customer loss. According to industry benchmarks, a significant portion of customer churn stems from poor service experiences — many of which could have been prevented. This negatively impacts key performance indicators like Net Promoter Score (NPS) and increases the risk of churn.
Proactive care, powered by AI, flips this model on its head. Instead of waiting for customers to complain, operators are able to detect, diagnose, and even resolve technical issues before they impact the user experience.
By resolving issues before they impact the customer experience, telecom operators can:
Boost NPS and customer satisfaction
Reduce operational and care costs
Improve first-call resolution (FCR) rates
Increase revenues by ensuring that services are operational/usable for as many customers as possible
Decrease the volume of incoming support requests
Lower customer churn

From Reactive to Predictive: AI at the Core
Tupl’s AI Care is leading the charge with a predictive and generative AI platform that not only monitors network behaviors in real time but also acts automatically when anomalies are detected. By integrating data across user records, network KPIs, system logs, and billing platforms, AI Care performs instant root-cause analysis — and where possible — triggers resolution workflows automatically.
This means that customer issues are often solved silently, behind the scenes, without the need for a single support call. When a call does come in, AI Care empowers agents with precise, plain-language insights, enabling first-call resolution and transforming the agent into a virtual telecom expert.
The Bigger Picture: A Fully Digitalized Expert System
The system digitalizes expert knowledge and automates the resolution of complex issues, making it available across care, engineering, and operations teams.
Acting as a virtual engineering agent, AI Care empowers customer service agents to respond like seasoned telecom professionals. Here’s how it works:
Predictive Intelligence
AI Care continuously monitors real-time data across multiple sources — from call detail records (CDRs) to provisioning logs and billing systems. This enables it to anticipate and detect anomalies before they turn into full-blown customer issues.
Automated Root-Cause Analysis
By collecting and correlating data from upstream and downstream databases (including node KPIs, system logs, and known alarms), AI Care uses state-of-the-art AI to instantly identify root causes.
Virtual Ticketing and Issue Tracking
Every detected issue is logged as a virtual ticket, enabling seamless tracking and trend analysis without any customer involvement.
Automated Resolution
AI Care goes a step further than just diagnosis. It can automatically trigger actions to resolve issues — such as reconfiguring network settings — often before the customer becomes aware there’s a problem.
Post-Resolution Validation
To ensure long-term resolution, the system performs follow-up validations after taking automated actions, confirming that the problem has been resolved.
Escalation and Reporting
In cases where an issue cannot be resolved automatically, AI Care generates detailed reports for engineering teams and alerts them to any abnormal patterns in virtual ticket trends.
Real-Time Support for Care Agents
When customers do call, care agents have instant access to dashboards that summarize ongoing and resolved issues. This allows them to provide clear, immediate answers during the first call — increasing FCR and enhancing the customer experience.
Visual Insight Turned Into Actionable Intelligence
AI Care contributes to improved direct feedback to the customer in real time — during the first call. This means customers no longer need to repeat their issues or wait for callbacks. Instead, care agents are equipped with AI-driven insights that allow them to explain and resolve problems on the spot.
Tupl AI Care turns first-line regular care agents into telecom experts — virtually. It positions them to deliver a high level of support and technical accuracy, usually reserved for engineering teams.
Making the Most Out of the Data: From First Line to Front Line Innovation
AI Care Proactive mode monitors the subscriber’s experience in near real-time to detect service impacting issues, automatically detecting and root causing customer problems by monitoring suspicious patterns from system logs, KPIs, alarmas, etc. . When an issue is detected, it creates a virtual ticket and, when possible, resolves the issue. When the issue cannot be resolved immediately, action recommendations can be forwarded to engineers for final decisions.
The real power of AI Care lies in its continuous learning loop. Detected issues are tracked through virtual tickets, validated post-resolution, and analyzed for trends. Dashboards provide real-time visibility for engineers and care teams, ensuring that no pattern of customer pain goes unnoticed. When automatic resolution isn’t possible, AI Care escalates issues with rich, actionable data for human intervention — keeping the service experience seamless.
Tupl’s First Line AI Care equips support agents with the digital tools to act like engineers — instantly. By bridging the gap between customer care and technical operations, operators can finally deliver the responsive, intelligent support that customers expect in the digital age.
Use Cases for Proactive AI Care
Below are key scenarios where AI Care delivers substantial value by anticipating and resolving issues before they affect customers:
- Maintenance Activities
AI Care detects degraded customer experience caused by network maintenance—such as equipment upgrades or cell site rehoming—and takes preemptive action (e.g. rerouting traffic, notifying support teams) to mitigate service disruption.
- Mobility & Ping-Pong Handovers
Frequent ping–pong handovers—when a device rapidly switches back and forth between cell sites—are typically a symptom of coverage instability. AI Care spots these patterns and automatically triggers remediation measures, improving handover performance and user experience.
- Performance Degradation
Chronic issues such as persistently high latency, packet loss, or recurrent alarms are quickly flagged by AI Care. It isolates root causes—like malfunctioning cells or overloaded sites—and initiates corrective workflows to prevent any drop in service quality.
- Coverage Holes
By analyzing customer locations across all radio bands, AI Care identifies and proactively addresses coverage gaps—whether outdoors or indoors—through optimization or targeted network expansion.
- Indoor Device Issues
Some customers experience poor service due to home router misconfigurations or WiFi repeaters. AI Care detects these indoor problems, guides users through fix recommendations, or escalates the issue with precise diagnostics.
- Provisioning & Configuration Conflicts
Misconfigured accounts—such as incomplete service setups—often lead to missing or limited functionality (e.g. SMS, VoLTE). AI Care spots these inconsistencies and either auto-remediates them or generates detailed tickets for agents to resolve.
- Account-related & Billing Issues
Idle or blocked profiles, unpaid services, and misrouted quotas can create support calls. AI Care flags such inconsistencies—like dormant accounts still consuming resources—and either corrects them or escalates with descriptive rootcause insights.
- EndUser Device Problems
Sometimes, the issue lies with the customer’s smartphone—such as unsupported frequency bands, rogue apps blocking system messaging, or firmware bugs. AI Care correlates device-level artifacts with network data to identify these problems, offering resolution guides or replacement recommendations.
Proactivity Is the New Standard
In a market where customer experience drives growth, solving problems before they reach the customer is no longer optional — it’s essential. With proactive AI care, telecom providers can delight users, streamline operations, and win the loyalty battle — one unseen issue at a time. preventing trouble before it hits customers and drastically improving satisfaction, NPS, and churn
The Impact on NPS and Churn
Resolving issues before customers notice isn’t just good service — it’s smart business. Proactive care significantly improves:
Based on real implementation in a Tier 1 Operator, implementing a proactive customer care process can have a strong business impact:
- Fewer calls to Customer Service (50%) for incidents with proactive actions in closed loop.
- Higher First Call Reolution (FCR) and Less Average Handling Time ( AHT) for incidences reported to Customer Care, increasing Customer satisfaction
- Increased Customer satisfaction and Churn reduction
- Full customer experience visibility with accurate root cause analysis provides the best Business Intelligence for technical actions
Conclusion
Proactive AI in customer care is no longer optional — it’s essential. Solutions like Tupl’s AI Care show how leveraging predictive intelligence, process automation, and seamless integration across systems can dramatically enhance the customer experience. By resolving issues before they escalate, telecom operators can strengthen loyalty, reduce churn, and maintain a competitive edge in a demanding market. Tier 1 Operators with the best customer care rankings are already leveraging AI to turn customer care into a strategic business function.
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