AI demands strain network infrastructure

Growing AI applications and data are pushing networks to their limits. Networks must now resolve faults and configuration issues rapidly without human help.

Meet agentic NetOps

Agentic NetOps uses AI to automate network responses by analyzing telemetry data and root causes in real time. It's the evolution from manual fixes to fully automated remediation.

Why networks can't afford human errors

A single misconfiguration can cascade across an entire network. Downtime costs are rising, security risks are growing, and infrastructure must respond faster than humans can.

“A single incorrect configuration has a huge ripple effect.”

Selector launches Foundry platform

Selector AI released Selector Foundry this week, a development platform that lets engineers build AI agents to correlate network signals and recommend fixes across multivendor environments.

Full-stack observability in one place

Foundry pulls telemetry from network devices, management software, and MCP tools into a single model. A reasoning layer then detects anomalies, diagnoses root causes, and suggests fixes.

Agents that take action

Selector's agents don't just identify problems, they fix them. The platform includes agents for reasoning, root-cause correlation, and incident management, plus integrations with ServiceNow, PagerDuty, Slack, Teams, and Jira.

“Selector's agents do more than find the problems, they take action!”

The deterministic challenge

Unlike most AI tools that use probability, Agentic NetOps must be deterministic because networks cannot fail. This makes building multi-step automation in hybrid environments extremely difficult.

What true Agentic NetOps requires

Organizations need a detailed platform to collect and analyze data from multiple network layers and sources. It must integrate data, agents, and correlation tools to drive both root-cause analytics and automated resolution.

From reactive to proactive management

Agentic NetOps shifts teams from responding to problems after they happen to preventing them before they start. This requires moving from manual oversight to autonomous, governed execution.

Measurable ROI from faster fixes

The return on investment is direct: solve errors faster, boost team productivity, and cut costs by reducing downtime. Selector's platform combines observability, root-cause analytics, and orchestration in one solution.