Every telecom operator knows these moments: a subscriber’s video call freezes mid-sentence. A streaming session buffers through the final episode. A payment app times out at checkout, all while across the operations center, every dashboard is green.
This is the customer experience gap in action. Infrastructure KPIs (RAN availability, interface throughput, core function health) can all sit comfortably within thresholds while individual sessions quietly degrade. The customer notices. The network does not. In most cases, the first signal the operator receives is a complaint, or worse, a silent churn.
Why CX Is Still a Guessing Game
Traditional service assurance was built to monitor the network, not the customer. It tracks component health and aggregates performance into averages, while many platforms also rely on traffic sampling, capturing only a fraction of user sessions. In today’s high-volume 5G networks, this creates critical visibility gaps where subtle, short-lived issues disappear, even though they’re often the ones that have the greatest impact on customer experience. The result is a disconnect: infrastructure KPIs may appear healthy while a customer’s video session degrades, leaving care teams to validate complaints with partial evidence and engineering teams chasing issues they can’t reproduce.
Agentic AI Won’t Close the Gap on Its Own
The introduction of agentic AI is changing this equation, but hurdles remain. According to the NVIDIA State of AI in Telecommunications, 2026 survey, 88% of organizations currently sit between Levels 1 and 3 on the TM Forum’s autonomous network maturity scale, while 41% expect agentic AI to drive their leap to Level 4. Unlike traditional AI, which stops at insights and recommendations, agentic AI has the potential to determine and execute the best course of action: AI agents perceive live data, reason about root causes, and act continuously, recommending and executing routine actions within operator-defined policies, with human validation on higher-impact actions.
Applied to customer experience, that shift could be transformative. Instead of waiting for a ticket, AI agents can watch every subscriber’s quality of experience (QoE) in real-time and flag early indicators of dissatisfaction before they escalate into complaints. In theory, this works seamlessly. In practice, it hinges on the piece of the puzzle many overlook: reliable, trusted data.
With telecom networks generating some of the largest and most complex datasets in any industry, customer information is certainly being captured. Yet this data rarely exists in any form that either agentic AI or humans can consume effectively. Even if the operator has all its data in one container, it still needs to be correlated across domains (RAN, core, and edge), which demands significant effort. While engineers have for decades compensated for this fragmentation through expertise, experience, and intuition, AI systems cannot. This is where next-generation assurance solutions come in.
RADCOM Neura Customer Experience Agents: Grounded in Trusted Customer Data
RADCOM Neura puts dedicated AI agents to work on exactly this problem. AI agents are only as good as the data they reason over, and that is the gap RADCOM Neura fills.
Anchored in RADCOM ACE, RADCOM’s intelligent assurance platform, RADCOM Neura Customer Experience Agents serve as a telecom-hardened funnel architecture that connects uncorrelated data across silos to the agentic solution. This helps the agent see which application flows are affected, on which network path, and for which subscriber segment. RADCOM analyzes 100% of traffic in real time, with no sampling, and correlates the data per subscriber and per session from the RAN through the core to the service layer. For the highest traffic volumes, RADCOM High-Capacity User Analytics (HCUA) delivers ultra-high-capacity, real-time user-plane analysis of up to 800 Gbps on a single COTS server.
This shifts customer experience management from reactive, ticket-based handling to proactive identification and mitigation. And since the agents detect, diagnose, and act in one continuous loop, issues that once took hours of manual troubleshooting are resolved far faster. These AI agents are not lab concepts; they are being evaluated in Tier-1 operators running 5G Standalone networks today. These include:
- RADCOM Subscriber Experience Analyzer measures the current network experience of a specific subscriber and assesses the probability that they will generate a complaint, turning churn risk into a signal operators can act on.
- RADCOM Complaint Validator checks a subscriber’s experience KPIs and searches for evidence that a reported problem actually exists in the data, giving care teams an objective, evidence-based view of what happened instead of anecdote.
- RADCOM Subscriber Impact Validator identifies which subscribers are affected by a network issue right now, and how many will be if it persists, so remediation can be prioritized by real customer impact rather than technical severity alone.
RADCOM Neura Customer Experience Agents transform a customer complaint into a query that the operator can answer with evidence, or fixes an emerging degradation before anyone calls the customer service line. And humans stay in the loop. RADCOM NetTalkTM GenAI powered conversational interface, lets teams query the data behind any agent recommendation, validate findings before automated actions execute, and trace every insight back to the subscriber-level data that informed it.
Experience Is the New Uptime
Subscribers don’t think in terms of network architecture; they think in “outcomes”: whether a video call holds, a payment completes, or an application responds instantly. Operators that give AI agents complete, real-time visibility into every subscriber’s experience will resolve issues before customers notice them. Those that don’t will keep discovering problems the old way: one frustrating complaint at a time.
For more information on RADCOM Neura Customer Experience Agents, or to schedule a demo, contact us at [email protected].
