Selector

What Selector does

Selector AI is an industry-leading AIOps platform designed to provide instant, real-time actionable insights for managing multi-domain network and application infrastructures. It unifies diverse data sources like logs, metrics, configs, and topology into a single AI layer to understand operations, automate insights, and reduce Mean Time To Resolution (MTTR). Selector's multi-layer AI continuously learns, reasons, and explains events in context, offering reactive intelligence through AI correlation and causation layers, and proactive intelligence via trends, prediction, and predictive analytics. The platform also features an LLM-powered copilot for natural language interaction and guided automations, and an operational digital twin for visualizing dependencies and preventing outages. It integrates with over 300 data sources and various ITSM and chat platforms to deliver actions and insights where work happens.

Key capabilities

• AI-powered network observability
• Unifies data (logs, metrics, configs, topology) into a single AI layer
• AI correlation & insights
• Operational digital twin
• Network LLM & copilot for natural language interaction
• Full-stack observability
• Multi-layer AI for learning, reasoning, and explaining events
• Ingest & enrich diverse data sources
• Learning & understanding normal behavior and log patterns
• Reactive intelligence with AI Correlation engine and Causation layer
• Proactive intelligence with trends & prediction and predictive analytics
• LLM-powered copilot for plain-language insights and guided automations
• Action layer for automated delivery to ITSM or chat platforms
• Feedback & Continuous Learning
• Connects to 300+ telemetry sources (network, cloud, edge)
• Collects metrics, logs, configs, and flows with no agents
• Caches and enriches data at the edge
• Normalizes, enriches, and unifies every signal into a consistent model
• Live querying and analysis at scale
• Builds a live knowledge graph for cause-and-effect reasoning
• Integrates with Slack, Teams, and ITSM tools
• Delivers context-rich alerts and recommendations
• Purpose-built AI models trained on network telemetry
• Cross-domain correlation across network, cloud, and application layers
• Conversational insight for natural-language questions
• Digital Twin for visualizing dependencies and simulating impact
• App-to-Infrastructure RCA
• Trace + log correlation
• Anomaly detection
• Synthetic + real-user monitoring
• Predictive analytics for releases
• Copilot for developers
• Executive-ready KPIs + dashboards
• Copilot for leadership
• Tool consolidation + cost reduction
• Secure, compliant architecture (SOC 2, ISO27001, GDPR-aligned)
• AI-Powered modernization roadmap
• Flexibility at enterprise scale (SaaS, hybrid, on-prem deployment options)

Use cases

• Reduce MTTR (Mean Time To Resolution)
• Troubleshoot network issues faster
• Avoid downtime
• Improve efficiency
• Cut through noise and simplify operations
• Improve observability across distributed hybrid networks
• Eliminate alert fatigue & automate incident triage
• Unify operational data & accelerate migration planning
• Build an operational twin for faster root cause analysis
• Debug faster and deliver more resilient releases for application developers
• Isolate true root causes by correlating logs, traces, and configs
• Understand where latency, loss, or API failures originate
• Catch issues before they spread
• Quantify uptime gains and operational efficiency
• Enhance performance, validate changes, and strengthen reliability
• Maintain always-on, high-performance systems for financial institutions
• Safeguard transactions and maintain low-latency performance
• Accelerate resolution by up to 95% with AI-driven correlation
• Detect and prevent issues before they impact customers or critical services
• Ensure flawless trading, payments, and transactions
• Maintain uptime in critical services
• Manage complex, hybrid environments
• Demonstrate audit readiness and compliance
• Reduce partner and 3rd-party operational risk
• Meet modern digital service demands
• Model capacity changes, failure points, and 'what-if' scenarios
• Strengthen operational resilience
• Find root cause faster and protect uptime by cutting through alert noise
• Improve visibility into infrastructure performance, risk, and efficiency for executives
• Enable AI-powered modernization
• Reduce downtime + risk
• Simplify toolchain
• Prove ROI at scale
• Forecast risks and identify opportunities for optimization
• Align technology visibility with digital transformation priorities
• Deploy in SaaS, hybrid, or on-prem environments

AI approach

Selector's multi-layer AI continuously learns, reasons, and explains, providing real-time clarity across every layer of network and application infrastructure. It unifies logs, metrics, configs, and topology into a single AI layer for correlation, insights, and an operational digital twin. The platform uses purpose-built models trained on real network telemetry to understand cause, context, and impact, and includes an LLM-powered copilot for natural language interaction and automation.

Tech named: AI, Machine Learning, LLM, AI Correlation engine, Predictive analytics, Network LLM, Network Language Model (NLM)

Industries served

• Software Development
• Financial Services
• Healthcare
• Media and Entertainment
• Telecommunications
• Hospitality
• Digital Infrastructure / Data Centers

What it says sets it apart

• AI-powered network observability solution
• Unifies every signal (logs, metrics, configs, topology) into a single AI layer
• AI continuously learns, reasons, and explains
• 95% noise reduction
• 10x faster RCA (Root Cause Analysis)
• 70% fewer incidents
• Operational digital twin for visualizing dependencies and predicting impact
• Network LLM & copilot for natural language interaction and automations
• Multi-layer AI understands relationships, behaviors, and intent
• Integrates with over 300 data sources
• Connects the dots to give answers instead of just alerts
• Purpose-built AI models trained on real network telemetry
• Cross-domain correlation across network, cloud, and application layers
• Domain-specific Network Language Model (NLM) for Copilot
• Unified view of application performance, infrastructure health, and user experience
• Seamless integration with existing APM, CI/CD, and telemetry stack
• AI-driven RCA summaries across applications, networks, and infrastructure
• Code-aware correlation for tracing performance or deployment regressions
• Automated plain-language updates for team channels and service reviews
• Built for financial resilience, ensuring ultra-low latency operations
• Predictive risk intelligence for financial institutions
• Operational twin modeling for 'what-if' analysis and capacity planning
• AI-native observability and correlation
• One shared operational view across network, infrastructure, and applications
• Natural language interaction instead of dashboards and queries
• Context-first correlation that reduces noise and confusion
• Built by people who have run real networks and supported real outages
• Platform-first mindset built for scale and reliability
• Strong customer momentum across enterprise and service provider environments
• Clear vision for autonomous, context-aware infrastructure operations
• Proven ROI + accelerated time-to-value
• Compliance built-in, not bolted-on

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.