Agentic AI
Unlocking the Era of Agentic Intelligence
Next-level network intelligence meets customer excellence
Agentic AI refers to a new class of artificial intelligence systems designed for autonomous decision-making and action, requiring little to no human oversight.
These systems integrate multiple AI models that can interpret data, initiate tasks, and respond dynamically to evolving conditions. Unlike conventional AI tools that simply provide recommendations, agentic AI goes further—it plans, decides, and executes actions independently, adapting in real time based on contextual data. Agentic AI agents operate autonomously and collaboratively, continuously collecting and interpreting data from diverse sources, including other agents, to manage complex, multi-step tasks.
Unlike traditional AI systems, they don’t just analyze patterns—they act on them. These agents proactively detect anomalies, make real-time decisions, and adapt their behavior to optimize outcomes, often surfacing insights and taking actions that conventional systems would miss. In the telecom domain, this evolution unlocks the potential for fully autonomous networks: systems that not only understand operational complexity but can prioritize actions, optimize performance, and self-adjust in real time to ensure exceptional customer experiences.
Transforming Network Data into Experience-Driven Decisions
RADCOM’s agentic AI leverages advanced computing capabilities to deliver real-time, granular-level data, including per-user, device, and service analytics. It provides a complete understanding of the network—from the RAN to the core—offering insights into user trends, location intelligence, usage patterns, service interactions, and more.
RADCOM’s end-to-end solutions monitor tens of millions of connected devices, high-speed voice and data services, and dynamic network conditions. This sheds light on both network and customer issues, delivering actionable insights across usage trends and service performance. By embedding an agentic AI layer, RADCOM enables operators to harness existing network data, generating reliable and trustworthy insights from real-time, balanced data models.
Driving Customer-First Networks
Emerging from our RADCOM Innovation Lab, two purpose-driven agentic AI solutions have been released which integrate with leading customer care, service management, and service orchestration platforms to facilitate fast complaint resolution. These AI agents analyze issues on the network, validate whether a complaint is reasonable and related to a network issue, correlate it with similar complaints, and suggest a resolution.
Accelerated Ticket Resolution
Agentic AI-powered automation enhances network operations by streamlining processes, such as complaint resolution, both during and after customer interactions. Background workflows interface with service ticketing platforms, enabling agents to process tickets assigned to the network. It analyzes complaints in raw text form, validates them by correlating with RAN and core network faults and relevant KPIs, and then prioritizes the most critical defect. This enables engineering teams to resolve serious issues quickly, before they escalate.
Predictive Complaint Resolution
Agentic AI Predictive Complaint Resolution automates transactions that help pre-empt issues that could lead to grievances. By applying predictive analytics and preemptive service optimization, along with specific service assurance data and subscribers’ KPIs, the agent generates a model that can then be applied to the whole subscriber base. This significantly enhances customer care and enables proactive mitigation of potential issues that may arise.
Benefits
Accelerate
resolution time
Enhance customer satisfaction
Decrease service
ticket volumes
