RADCOM Launches Neura, an AI Agent Suite Designed for Integration into Agentic AI Ecosystems
Leveraging AI agents and real-time customer experience insights to power autonomous, intelligent networks
RADCOM Neura utilizes real-time customer-focused data from RADCOM ACE, combined with a comprehensive suite of AI and machine learning tools, to power a team of specialized AI agents. These agents operate independently across network operations, service assurance, and customer care, helping operators improve efficiency, reduce operational overhead, and consistently deliver better subscriber experiences. Built with guardrails, RADCOM Neura ensures AI-driven actions remain explainable, governed, and aligned with operator-defined policies and regulatory requirements.
"We are enriching agentic AI ecosystems that understand intent, operate independently, and directly connect network insights to customer outcomes," said
By seamlessly integrating with service management, Operations Support Systems (OSS), and Business Support Systems (BSS), RADCOM Neura creates a unified source of truth that links network performance to customer impact. RADCOM Neura automates case validation, service quality analysis, root-cause analytics, and customer experience improvements, enabling operators to increase first-call resolution, reduce ticket volume, accelerate resolution times, and improve customer satisfaction.
Telecom operators are evolving from raw data to insights, and from insights to intelligent, autonomous actions that improve customer experience and operational efficiency.
All AI agents within RADCOM Neura support the Model Context Protocol (MCP) for standardized, secure data access and Agent-to-Agent (A2A) communication. This open, interoperable architecture enables seamless collaboration among AI agents, coordinated decision-making, and closed-loop automation across network operations. By supporting MCP and A2A, RADCOM Neura allows telecom operators to leverage existing AI and agentic AI infrastructure, data sources, and prior investments, while accelerating integration into operational environments and reducing the risk of vendor lock-in.
Autonomous AI Across the Network from RAN to Core
RADCOM Neura transforms real-time network data into autonomous intelligence that identifies service quality, user behavior, and performance issues throughout the entire network, from the Radio Access Network (RAN) to the core. Using model context and agent-to-agent collaboration protocols, RADCOM Neura's AI agents automate service assurance, network operations, and customer support tasks, while seamlessly integrating with platforms such as ServiceNow and other service management tools to enhance workflows and accelerate outcomes.
This unified approach minimizes manual work for engineering and operations teams, shortens the average time to resolve issues, and ensures quicker, more precise responses to customer-impacting problems.
AI-Ready Data Infrastructure
An intelligent, automated network requires real-time visibility across all devices, network elements, and services.
One Suite, Many Expert AI Agents
RADCOM Neura is designed around a team of specialized AI agents, each dedicated to a specific domain to provide higher accuracy, faster insights, and improved operational results. Unlike single, general-purpose AI models, RADCOM Neura's agents work in parallel, are easier to validate and manage, and can be scaled or upgraded independently. Multiple agents collaborate in real time, such as validating a customer complaint, assessing whether other subscribers are affected by the same issue, and automatically conducting root cause analysis to accelerate resolution and enhance outcomes.
RADCOM Neura's AI agents are categorized into three main areas:
Customer Experience Agents
Provide real-time visibility into each subscriber's journey, validate complaints using live network data, identify dissatisfied users, and enable proactive, personalized customer care.
Service Quality Agents
Automatically validate incidents, confirm impacted subscribers, eliminate false alarms, and speed up resolution to maintain service reliability and operational efficiency.
Network Optimization Agents
Continuously analyze network performance, identify root causes and bottlenecks across the RAN and core, and recommend optimized actions to create a more efficient, self-optimizing network.
Through collaborative model context sharing, these agents build a comprehensive understanding of network behavior and customer impact, enabling explainable, reliable, and tailored AI for real-world telecom operations.
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For all investor inquiries, please contact:
Investor Relations:
FNK IR
rdcm@fnkir.com
646-809-4048/312-809-1087
Company Contact: Hod Cohen
CFO+972-3-645-5055
hod.cohen@radcom.com
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Designed to be open, vendor-neutral, and cloud-agnostic,
Risks Regarding Forward-Looking Statements
Certain statements made herein that use words such as "estimate," "project," "intend," "expect," "believe," "may," "might," "potential," "anticipate," "plan," or similar expressions are intended to identify forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and other securities laws. For example, when the Company discusses RADCOM Neura, its AI Agent Suite, and the expected benefits thereof, it is using forward-looking statements. These forward-looking statements involve known and unknown risks and uncertainties that could cause the actual results, performance, or achievements of the Company to be materially different from those that may be expressed or implied by such statements, including, among others, changes in general economic and business conditions and specifically, decline in demand for the Company's products, inability to timely develop and introduce new technologies, products, and applications, loss of market share and pressure on prices resulting from competition and the effects of the conflict in
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