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Netscout Systems has announced the extension of its Omnis AI Insights solution to communications service providers (CSPs), enabling operators to convert raw network data into AI-ready smart data to support the deployment of AI agents across customer experience and network operations.
The development comes as telecom operators scale artificial intelligence initiatives. Citing a McKinsey & Company C-level survey of telco operators, Netscout said 64% of respondents are expanding their AI programmes, with AI agents identified as a central driver. However, 45% pointed to data constraints as the primary barrier to scaling AI adoption.
“AI agents only deliver meaningful outcomes when they are powered by meticulously curated, multi-domain intelligence drawn from real activity across the digital ecosystem,” said Richard Fulwiler, Senior Director, Product Management, Netscout.
“By reducing data volume, complexity and infrastructure demands for storage and processing, while enhancing network security, we help CSPs shift customer service and care from being a cost centre to a strategic resource that protects revenue and strengthens loyalty,” he added.
AI-Ready Smart Data for Telecom Networks
According to Netscout, the Omnis AI Sensor for service providers delivers curated, real-time smart data derived from network transactions and their relationships.
The sensor collects granular operational intelligence using Deep Packet Inspection-derived insights at source, across mobile and fixed environments.
As detailed in the company’s data sheet, the Omnis AI Sensor captures metrics such as application response times, latency, and throughput. It supports visibility across 5G standalone, RAN, core, multi-access edge computing, transport, FTTx and wireline networks.
Use cases include subscriber experience management, service chain automation, network quality analytics, 5G slicing SLA monitoring, OTT classification, and network security.
Netscout said the platform correlates data across the network into a unified, consistent view, enabling CSP teams to link activity directly to subscriber experience.
By intelligently normalising network information and aligning events across domains, operators can conduct faster root-cause analysis and make operational decisions with clearer visibility of service impact.
Omnis AI Streamer Enables Scalable AI and Automation
Complementing the sensor, the Omnis AI Streamer for service providers converts high volumes of network telemetry into curated, programmable data streams tailored for network operations, service assurance and automation teams.
According to the company, the Streamer organises extracted metadata and session-level data into structured playbooks to enable efficient data lake ingestion or streaming through pipelines to ecosystem platforms.
Optional machine learning-based enrichment, including outlier detection and contextual classification, can be applied to selected feeds.
By extracting, aggregating and labelling high-value signals, the Streamer produces smaller, faster-to-process datasets that external AI agents, analytics platforms and operational applications can consume directly to support closed-loop automation.
Deployment options include standalone Omnis AI Sensor instrumentation for new customers and adaptor models for existing InfiniStreamNG and vSTREAM deployments, allowing CSPs to extend current infrastructure investments while introducing AI-focused workflows.
Netscout stated that the architecture supports large-scale service provider networks with end-to-end observability, including user-plane traffic and subscriber-level intelligence.