Selector
AI-powered full-stack observability for intelligent issue detection & resolution
What is Selector? Complete Overview
Selector is an AIOps platform that delivers full-stack observability across network, infrastructure, and applications. It provides real-time insights, automated root cause analysis, and closed-loop automation to resolve issues faster. The platform connects data from 300+ sources, using machine learning to correlate events and reduce alert noise. Designed for enterprise IT teams, network operations centers, and cloud service providers, Selector transforms traditional monitoring with its patented correlation engine, digital twin technology, and network-specific language model (LLM). The solution dramatically improves operational efficiency, with customers reporting 75:1 reduction in ticket volume and 85% faster mean time to detect issues.
Selector Interface & Screenshots
Selector Official screenshot of the tool interface
What Can Selector Do? Key Features
Patented Correlation Engine
Selector's AI-powered correlation automatically connects symptoms to root causes across all infrastructure layers in seconds, eliminating manual troubleshooting. The engine requires no rules or thresholds, reducing alert fatigue by 95% while increasing accuracy. It consolidates multiple alerts into actionable incidents with full context.
Digital Twin Technology
The platform maintains a continuously updated virtual model of your entire environment - including infrastructure, network topology, cloud services, and dependencies. This enables what-if scenario planning, impact analysis, and disaster recovery simulations with real-time accuracy.
Network LLM & Copilot
Selector Copilot is the industry's first network-specific language model that allows engineers to investigate issues using natural language. Integrated directly into chat tools and CLI, it provides plain-language explanations, summaries, and remediation suggestions based on actual operational telemetry.
Full-Stack Observability (L1-L7)
Unlike disjointed monitoring tools, Selector provides unified visibility across all layers - from physical infrastructure to application performance. The platform ingests and correlates data from logs, metrics, configs, traces, and flow data regardless of source.
Closed-Loop Automation
Selector doesn't just identify problems - it enables automated remediation through API-triggered workflows. The system can suggest and execute fixes directly from chat interfaces like Slack or Microsoft Teams, turning insights into immediate action.
Best Selector Use Cases & Applications
Critical Service Outage Investigation
When a customer-facing application slows down, Selector correlates metrics from servers, network paths, and application traces to pinpoint a misconfigured load balancer as the root cause within minutes, reducing MTTR by 85% compared to manual processes.
Cloud Migration Planning
IT teams use Selector's digital twin to simulate workload migrations between data centers and cloud providers, predicting performance impacts and identifying dependency risks before execution.
Network Capacity Planning
By analyzing historical traffic patterns and current utilization, Selector identifies impending bandwidth bottlenecks and recommends optimal upgrade paths, preventing service degradation.
How to Use Selector: Step-by-Step Guide
Connect Data Sources: Integrate Selector with your existing monitoring tools, network devices, and cloud services. The platform supports 300+ out-of-the-box integrations including SNMP, NetFlow, APIs, and agent-based collection.
Data Processing & Correlation: Selector's ML engine automatically processes incoming telemetry, establishing relationships between infrastructure components and services. The system begins building your digital twin and identifying patterns.
Incident Detection: The correlation engine identifies anomalies and connects related events across domains, transforming raw alerts into contextualized incidents with probable root causes.
Investigation & Resolution: Use Selector Copilot to query incidents in natural language or examine visual dependency maps. The system provides remediation suggestions that can be manually approved or automatically executed.
Selector Pros and Cons: Honest Review
Pros
Considerations
Is Selector Worth It? FAQ & Reviews
Selector goes beyond threshold-based alerting by using AI to understand relationships between infrastructure components and automatically correlate symptoms to root causes across domains, eliminating manual investigation.
The platform works across on-premises data centers, cloud environments (AWS, Azure, GCP), hybrid architectures, and edge deployments, maintaining consistent observability regardless of location.
Most customers achieve initial value within weeks thanks to extensive out-of-the-box integrations and auto-discovery capabilities that minimize configuration requirements.
No - Selector enhances existing investments by aggregating and correlating data from tools you already use like Splunk, Datadog, or SolarWinds, providing higher-level insights they can't deliver individually.
Yes - while incorporating general networking knowledge, the Copilot continuously learns from your unique telemetry to provide answers and recommendations tailored to your infrastructure.
