NETSCOUT SYSTEMS, INC. has made a big announcement. The company now adds Model Context Protocol (MCP) connectivity for its Omnis™ AI Insights solution. This enables AI assistants and agents to consume AI-Ready Smart Data on demand. Thus, the artificial intelligence systems can make better decisions based on real-time operational evidence. This means that companies get trusted context for critical operations.
NETSCOUT is known for its observability, AIOps and cybersecurity solutions. The company also provides good DDoS attack protection. So this new MCP integration is built on solid ground.
NETSCOUT’s patented Adaptive Service Intelligence™ (ASI) technology powers the AI-Ready Smart Data framework. More precisely, it leverages granular data to build richer network intelligence. NETSCOUT also extracts the semantics at the source. This process turns raw ASI data into dense, AI-ready formats. So downstream systems get cleaner, more useful information.
This change is due to two factors. First, Omnis Sensor captures application, service and behavioral context in real-time. It creates important metadata but also retains operational meaning. In the meantime, Omnis Streamer gathers and curates this AI-Ready Smart Data for future use. Playbooks can be customized to adapt data for healthcare, finance and telecom. Furthermore, a new built-in MCP server provides AI agents with direct access to datasets.
How AI-Ready Smart Data Strengthens Decision-Making
This enrichment process reduces telemetry volume before data reaches AI models. As a result, processing costs and complexity drop significantly. At the same time, AIOps, security, and analytics systems gain more meaningful evidence. Thus, organizations move closer to reliable, autonomous operations.
Phil Gray, AVP of product management at NETSCOUT, addressed the update. He said: “Everyone knows there is no value to conclusions that cannot be trusted. By adding MCP tools alongside our existing Kafka streaming capabilities, Omnis AI Insights gives IT professionals the flexibility to feed AI-ready Smart Data into analytics and AI platforms at scale and cost effectively, while also making that same context-rich intelligence directly accessible to Models and Agents. This helps organizations power AI with a compact, curated, trusted source of network truth rather than fragmented operational signals that suffer from hallucinations and high token spends.”
In one live deployment, standard monitoring tools missed a real problem. Network conditions degraded user experience despite showing zero application errors. However, NETSCOUT’s Smart Data captured critical details instantly. These included retransmit counts and zero-window events. Therefore, AI could verify facts instead of guessing outcomes.
Ultimately, NETSCOUT AI-Ready Smart Data helps teams reach accurate answers faster. It also lowers token and infrastructure expenses considerably. Additionally, it extends value from existing NETSCOUT investments. Consequently, businesses can innovate without rebuilding entire data pipelines.
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News Source: Businesswire.com
