Gilat becomes first to market with AI-powered network management system
- Satellite Evolution Group

- Sep 11
- 1 min read

Gilat Satellite Networks has announced the AI transformation of its Network Management System (NMS), integrating Model Context Protocol (MCP). The new AI capabilities are available immediately.
This integration introduces a new NMS-MCP, which acts as a gateway between the NMS and AI agents. The NMS-MCP supports authentication, licensing, and secure communication, ensuring compliance and operational integrity. AI Models of GPT Series 4, 5 and 5 mini as well as o3, o4, o4 mini and Claude Sonnet 4 are available for interfacing to the Total-NMS.
Examples of AI Use Cases Enabled:
NOC AI Agent: An AI-driven Network Operations Center (NOC) agent can continuously monitor system health, detect anomalies, and take proactive measures. For example, in case of performance degradation or resource bottlenecks, the agent can automatically trigger corrective actions such as restarting services, reallocating resources, or escalating issues to human operators when necessary.
SDS AI Agent: For Software-Defined Satellite (SDS) environments, an AI agent can dynamically adjust network configurations based on business priorities, traffic patterns, and service-level agreements. This ensures optimal resource utilization and improved Quality of Service (QoS) for end-users.
“We see AI as a critical business multiplier for our customers. It will enable our customers to innovate more rapidly and manage their networks with greater simplicity,” said Aharon Mullokandov, Chief R&D Officer at Gilat. “This milestone demonstrates our clear leadership in deep SATCOM technology and our commitment to addressing the business needs of our customers. It is just the first step in our AI transformation. Stay tuned as we plan more to come.”



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This is a fascinating development from Gilat! 🚀 The integration of AI into network management systems shows how quickly SATCOM and AI are converging. The introduction of the NMS-MCP feels like a real game-changer—having AI agents monitor, detect anomalies, and even self-correct in real time could drastically reduce downtime and improve operational efficiency.
I especially like the example of the NOC AI Agent—it highlights how proactive automation can prevent small issues from escalating into major problems. For anyone following AI innovation across industries, this feels very similar to what’s happening in other digital ecosystems: autonomous adjustments, predictive monitoring, and smart allocation of resources.
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