Selector AIOps

Selector transforms complex, fragmented operational data into actionable intelligence with advanced AI and machine learning. That platform ingests and unifies logs, metrics, events, and configuration data from virtually any source across hybrid, multi cloud, and on premises environments into a single, correlated view. This eliminates the need for multiple point tools, reduces operational silos, and gives IT operations teams single pane real time visibility into their entire infrastructure.

At the core of Selector are three powerful capabilities designed to simplify and accelerate network and infrastructure operations. Selectors Network Language Model (NLM) and Copilot allow teams to interact with their environments using natural language, querying telemetry and historical data directly through Slack, Teams, API, or directly in the Selector UI. Correlation and Root Cause Analysis (RCA) automatically connects metrics, logs, and events to identify patterns, reduce alert noise, and pinpoint the true source of incidents, dramatically reducing mean time to resolution (MTTR). Meanwhile, Digital Twin modeling creates a dynamic, topology aware map of networks and infrastructure, enabling IT teams to visualize dependencies, anticipate risks, and make data driven decisions for capacity planning and performance optimization.

By combining conversational AI, automated ML driven correlation, and predictive modeling, Selector empowers IT teams to move from reactive firefighting to proactive operations. Teams can identify anomalies earlier, resolve incidents faster, and even prevent outages before they occur. Whether deployed on premises, in the cloud, or delivered as SaaS, Selector seamlessly integrates with existing ITSM, SIEM, and automation platforms including ServiceNow, Jira, Splunk, and PagerDuty so users can ensure greater uptime, improve service reliability, and simplify network operations at scale.