An AI customer care solution that solves problems before they arise

AI customer care is necessary in an era defined by network complexity

Customer dissatisfaction with network services is a persistent issue for telecommunications providers. An estimated 50% of customer interactions focus on service quality concerns. Generative AI (GenAI) has been hailed as a transformative technology for customer care – however, its success depends on more than just natural language processing capabilities. Effective solutions must seamlessly link understanding customer interactions with accurately diagnosing network issues. Achieving this integration is a crucial step in deploying AI customer care. This transforms a reactive, resource-intensive function into a proactive and strategic driver of business value.

How AI customer care systems operate

The GenAI-driven customer care for multichannel business Catalyst integrates predictive and Generative AI as well as use of AI agent frameworks with TM Forum standards. Together, these create a fully automated, end-to-end AI customer care system. This solution combines rapid issue detection with personalized, channel-specific responses. It delivers a seamless experience for customers and operational efficiencies for providers.

At the back end, predictive AI identifies potential network issues by analyzing data from over 30 sources. These include network topology, MMS and RCS records, voice CDRs, and user profiles. Tupl’s AI platform evaluates this data to detect anomalies and predict disruptions before customers notice them. Once identified, the platform calculates the impact on services and prioritizes actions based on SLAs and business needs.

The next step involves Alvatross’ OSS executing corrective measures recommended by the predictive system. Tupl then verifies the resolution and assesses its effectiveness. Meanwhile, Qvantel’s BSS platform manages customer communications. The platform uses AI agents to evaluate the business impact and breached SLAs and initiates appropriate actions. Customers receive proactive updates through natural language responses generated by GenAI. These updates provide reassurance and help reduce inbound complaint volumes.

In terms of customer engagement and reporting, GenAI adds customer-centric interaction. The system creates context-aware responses tailored to individual needs. It ensures communication is clear and accurate. For complex issues, it acts as a copilot for human customer care agents, providing decision support and streamlined workflows. It also offers real-time access to critical data. This integration enables care teams to focus on relationship building, while AI handles repetitive and technical queries.

TM Forum standards, such as TMF621 and TMF641 APIs, ensure interoperability across platforms and enable seamless data exchange and system integration. Their use accelerates deployment, reduces complexity, and ensures scalability. As a result, the solution is suitable for wholesale, assisted, and end-user care models.

Bringing new value to customer care

This approach has immediate implications for the telecommunications sector - predictive AI minimizes service disruptions, while GenAI turns customer interactions into opportunities for engagement and revenue. These capabilities help CSPs to reduce churn, improve net promoter scores, and capture upselling opportunities. For CSPs, the impact could be seismic. Research estimates operational costs can be reduced by up to 70%, while issue resolution times can also be significantly shortened. Upselling opportunities also increase, as customer interactions shift from problem resolution to proactive engagement. And, by adhering to TM Forum standards, the solution provides a scalable and adaptable framework.

With this innovation, customer care evolves into a strategic advantage. Once seen as a cost burden, it now becomes an opportunity to foster loyalty, build lasting relationships, and create meaningful value for both businesses and customers.