Selector
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About
Selector is an advanced AI-powered network observability and AIOps platform designed to unify disparate data streams across modern hybrid environments. It addresses the growing complexity of large-scale networks by ingesting diverse data sources, including logs, metrics, configurations, and topology, into a single intelligence layer. The primary goal is to help operations teams cut through the noise of thousands of alerts to identify and resolve critical issues before they impact end-users. By using patented AI correlation, the system moves beyond simple monitoring to provide deep reasoning and explanation of every event in its proper context, helping teams understand why an incident occurred rather than just when. The platform functions through a multi-layered AI architecture that starts with ingestion and enrichment. It connects to over 300 data sources, learning normal behaviors and clustering logs into meaningful patterns without requiring manual rules or threshold tuning. Key features include an Operational Digital Twin, which visualizes dependencies and simulates "what-if" scenarios, and an AI-driven correlation engine that pinpoints the actual root cause of incidents. The system also includes a Network LLM and Copilot, allowing engineers to interact with their telemetry data using plain English queries via chat platforms like Slack or Microsoft Teams. This tool is specifically engineered for SRE leaders, Network Engineers, and IT Operations teams within large-scale industries such as telecommunications, financial services, healthcare, and retail. It is particularly effective for organizations managing thousands of sites or complex data center migrations where traditional manual monitoring falls short. High-profile users like Comcast and Bell utilize Selector to manage infrastructure at scale, benefiting from its ability to provide end-to-end visibility from Layer 1 to Layer 7. What differentiates Selector from legacy monitoring tools is its shift from reactive alerting to proactive intelligence. While traditional tools often require constant rule tuning and manual correlation across fragmented dashboards, Selector offers an AI-native anomaly detection system that requires zero tuning. Its ability to provide actionable insights and automated fixes directly within existing workflows allows teams to achieve significantly faster response times. The platform's rapid deployment model, which promises live integration within weeks despite high complexity, further sets it apart in the enterprise observability market.
Pros & Cons
Reduces mean time to repair (MTTR) by up to 85% for complex network issues.
Provides native integration with over 300 data sources including logs and metrics.
Offers a plain-English query interface through its integrated LLM copilot.
Reduces operational alert noise by approximately 95% via patented AI correlation.
Delivers real-time topology mapping through a live operational digital twin.
Lacks transparent public pricing models, requiring a demo request for cost details.
Primarily designed for large enterprise environments rather than small-scale networks.
Full implementation and integration across the stack typically take several weeks to complete.
Use Cases
Network Engineers at global telecom carriers can automate correlation across tens of thousands of devices to reduce alert noise.
IT Operations teams in retail can maintain uptime across thousands of physical locations using real-time topology mapping.
SREs at fintech firms can use unified visibility and automated data correlation to accelerate complex data center migration timelines.
Hospitality IT leaders can unify telemetry across wired and wireless networks to troubleshoot site-specific issues 85% faster.
NOC Service Engineering Supervisors can leverage predictive analytics to identify patterns and trends to optimize resource allocation.
Platform
Features
• anomaly detection
• root cause analysis
• automated remediation
• full-stack visibility
• 300+ data integrations
• network llm copilot
• operational digital twin
• ai correlation engine
FAQs
What kind of data sources can Selector ingest?
Selector supports over 300 integrations, including logs, metrics, configurations, flows, and APIs from both on-premise and cloud environments. It unifies these diverse signals into a single model for AI reasoning.
How does the AI Copilot help with network troubleshooting?
The Network LLM allows users to ask questions about their network status in plain English. It translates complex telemetry and dashboards into clear, actionable insights or safe, guided automations.
Can Selector help reduce the volume of alerts?
Yes, the platform uses patented AI correlation to cluster logs and related events, resulting in up to 95% reduction in alert noise. This helps teams focus on the root cause rather than individual alerts.
Is it possible to see the impact of network changes before they happen?
Selector includes an Operational Digital Twin that allows teams to visualize dependencies and perform what-if simulations. This feature helps predict the potential impact of changes or failures.
How long does it typically take to deploy the platform?
Unlike traditional tools that can take months to configure, Selector is designed for rapid deployment. Most teams can integrate their data sources and be live within a few weeks.
Pricing Plans
Enterprise
Unknown Price• 300+ data integrations
• Network LLM and Copilot
• Operational Digital Twin
• AI Correlation Engine
• Full-stack L1-L7 observability
• Automated incident remediation
• Predictive analytics
• Custom anomaly detection
• 24/7 Enterprise support
Free Trial
Free Plan• Core AI features
• Selected integrations
• Access to support portal
• Product documentation
• Learning center access
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
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