Selector AI announced a series of innovations, including a Network Language Model (NLM), enhanced digital twin capabilities, and programmable synthetics.
These advancements are designed to help businesses reduce operational complexity, resolve issues faster, and accelerate decision-making through AI-powered insights.
Selector AI's platform is a 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.
"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:
- 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.
- 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.
- 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.
"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."
To meet this increasing demand, Selector AI is expanding its global footprint, with new offices across the US, Canada, India, and Japan, ensuring it continues to deliver cutting-edge AI and machine learning solutions to IT operations teams worldwide.
The Latest
Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...
New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...
Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...
AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
If you were lucky, you found out about the massive CrowdStrike/Microsoft outage last July by reading about it over coffee. Those less fortunate were awoken hours earlier by frantic calls from work ... Whether you were directly affected or not, there's an important lesson: all organizations should be conducting in-depth reviews of testing and change management ...
In MEAN TIME TO INSIGHT Episode 11, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Secure Access Service Edge (SASE) ...
On average, only 48% of digital initiatives enterprise-wide meet or exceed their business outcome targets according to Gartner's annual global survey of CIOs and technology executives ...
Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...
