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Selector AI Unveils Industry-First Network Language Model to Transform Root Cause Analysis and Accelerate AI Adoption

Selector

New Release Enhances AI-Driven Insights, Reduces Downtime, and Empowers IT Operations Teams with Unified AIOps Solutions

Selector AI, the leader in network and infrastructure AIOps, today announced a series of novel innovations, including the industry’s first Network Language Model (NLM), enhanced digital twin capabilities, and programmable synthetics. These advancements are designed to help businesses drastically reduce operational complexity, resolve issues faster, and accelerate decision-making through AI-powered insights.

Selector AI’s platform remains the only unified AIOps solution that consolidates monitoring, observability, and multi-domain operations into a single, easy-to-use interface, eliminating the need for multiple disjointed tools.

Also Read: For True End-to-End Process Automation: Evolve Your Data Strategy and Architecture

“With our new Network Language Model, businesses can now gain real-time, actionable insights using intuitive natural language processing, enabling teams to streamline operations, slash mean time to detection and resolution (MTTD/MTTR), and improve overall network reliability,” said Nitin Kumar, Co-founder and CTO of Selector AI. “This release allows enterprises to leverage their data like never before, offering AI-driven analytics at their fingertips to help reduce downtime and enhance productivity.”

Key Business Benefits of the New Release:

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  1. Network Language Model (NLM): Empowering operations teams to make faster, data-driven decisions by correlating alerts with AI-driven insights from email notifications, maintenance logs, and other sources—minimizing false positives and improving alert accuracy. This reduces manual intervention and ensures critical issues are resolved faster.
  2. Enhanced Digital Twin Technology: Enable IT teams to predict network behavior through “What-If” scenarios, driving better risk management and faster problem resolution across all network layers. IT teams can now anticipate failures before they happen, improving uptime and customer satisfaction.
  3. Programmable Synthetics Sensors: Providing visibility into application performance and availability while seamlessly correlating this data with network infrastructure. These programmable sensors enable businesses to detect and resolve application performance issues before they impact end users, protecting revenue and ensuring a seamless user experience.

Also Read: AiThority Interview with Dr. Arun Gururajan, Vice President, Research & Data Science, NetApp

“Operational efficiency is critical to businesses facing increased outages and growing complexity,” said Kevin Kamel, VP of Product Management at Selector AI. “With these new capabilities, businesses can proactively prevent downtime, mitigate customer-impacting issues, and ensure service reliability through advanced analytics and sophisticated device modeling.”

Business Growth and Global Expansion

Selector AI’s advanced capabilities have already resulted in significant contracts with global enterprises, telecoms, and cloud providers, including major wins in India and Japan. The company is also making strides in the healthcare sector, where the demand for AI-based operational solutions continues to grow.

To meet this increasing demand, Selector AI is expanding its global footprint, with new offices across the US, CanadaIndia, and Japan, ensuring it continues to deliver cutting-edge AI and machine learning solutions to IT operations teams worldwide.

Also Read: AiThority Interview with Dr. Arun Gururajan, Vice President, Research & Data Science, NetApp

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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