The Selector Platform

Purpose-built ML & AI, trained and proven in the world’s most operationally demanding networks and infrastructure

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Autocorrelation and RCA for Proactive Detection and Remediation

The process starts with normalization. Metrics are auto-baselined, with any dynamic threshold violations being noted. These violations are internally handled as metadata rich events by the system.

Logs are processed using a proprietary log model. Patterns are automatically identified, and clustering applied. Metadata related to the types and rates of each log type are captured by the system. This data similarly is reduced down to events by the system.

From there, temporal and metadata based correlations are performed, allowing relationships between the various types of data to be surfaced. These correlations ultimately result in various insights that power the collaboration aspects of the Platform.

Fast-Track Remediation with Autocorrelation & Root-Cause

Collect and analyze telemetry from across your IT environment, detect anomalies and emerging incidents

Leverage causal ML to automatically correlate anomalies, identify the probable root cause, and enable faster incident response

Suppress noisy and redundant alerting, decrease alerting volume, and free the team to prioritize, triage, and resolve incidents faster

Facilitate Adoption with an Integrated LLM and Copilot

Democratize access to platform insights through an integrated LLM and conversational assistants, empowering users to query by natural language

Surface insights using plain language—no need to learn arcane query languages; empower your team to explore metrics, logs, and events like never before

Integrate with your preferred ChatOps platform, Slack, Teams, Zoom, and others, enabling proactive insights on the go, from any device

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Forget Wireshark. Now you can chat with your packets with Selector Packet Copilot.

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Simulate, Predict, and Optimize with a Digital Twin

Model network, infrastructure, and services to understand and contextualize past, current, and future behavior

Simulate and explore “What If” scenarios, predict failures, forecast capacity needs, and optimize resource allocation using the digital twin

Analyze resource consumption and component failures to identify single points of failures, optimize IT performance, and proactively mitigate bottlenecks