{"id":20747,"date":"2026-09-24T19:04:28","date_gmt":"2026-09-25T02:04:28","guid":{"rendered":"https:\/\/selectoraistg.wpengine.com\/?p=20747"},"modified":"2026-09-24T19:04:31","modified_gmt":"2026-09-25T02:04:31","slug":"introducing-selector-foundry","status":"publish","type":"post","link":"https:\/\/www.selector.ai\/ja\/blog\/introducing-selector-foundry\/","title":{"rendered":"Introducing Selector Foundry: Agentic NetOps"},"content":{"rendered":"\n

Network operations teams have heard plenty about AI this year. Most of it answers the alert in front of it, then hands the rest of the incident back to an engineer. Someone still has to correlate the evidence, find the cause, prepare the fix, and prove it held.<\/p>\n\n\n\n

This week, we announced Selector Foundry, the agentic NetOps solution built into the Selector platform. Foundry adds a team of specialized AI agents on top of the full-stack observability and AIOps foundation our customers already run. The agents correlate evidence, identify the root cause, act within guardrails your administrators define, and validate recovery. They do all of it from one correlated model of your entire infrastructure path.<\/p>\n\n\n\n

The goal is simple: put your best network engineer on every shift.<\/p>\n\n\n\n

Foundry ships with six generally available agents. Rosetta is the conversational interface that orchestrates them. Five specialists handle correlation, ticketing, notifications, dashboards, and building new agents. Teams can also author their own agents, version them in Git, test them against past incidents, and run them on their own data.<\/p>\n\n\n\n

The foundation underneath the agents<\/strong><\/h2>\n\n\n\n

An AI agent is only as reliable as the data it reasons over. If you point a language model at raw telemetry and ask what happened, you get a guess, because network data is high-volume, spread across vendors, and full of symptoms that look like causes.<\/p>\n\n\n\n

Selector Foundry agents start from context the platform has already finished. Selector collects telemetry from more than 300 sources, vendor-neutral, and normalizes it into one model. It detects anomalies, correlates them across domains, and uses topology to separate the causal fault from its downstream symptoms. By the time an agent begins work, the platform has already narrowed millions of data points to one incident with a named root cause.<\/p>\n\n\n\n

This is why Foundry agents give consistent answers that trace back to evidence. It also means there is nothing to rip and replace: Foundry runs on the collection and correlation you already have.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Two ways the work starts<\/strong><\/h3>\n\n\n\n